{"id": "paper:arxiv:2606.02800", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Cosmos 3: Omnimodal World Models for Physical AI", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Cosmos 3: Omnimodal World Models for Physical AI (2606.02800).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02800", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02060", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories (2606.02060).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02060", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03577", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching (2606.03577).", "popularity": {"value": 4, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03577", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01993", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MMG2Skill: Can Agents Distill In-the-Wild Guides into Self-Evolving Skills?", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for MMG2Skill: Can Agents Distill In-the-Wild Guides into Self-Evolving Skills? (2606.01993).", "popularity": {"value": 4, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01993", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.04527", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation (2606.04527).", "popularity": {"value": 3, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.04527", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2606.03031", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification (2606.03031).", "popularity": {"value": 3, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03031", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.04513", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation (2606.04513).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.04513", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03746", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Qwen-Image-Flash: Beyond Objective Design", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Qwen-Image-Flash: Beyond Objective Design (2606.03746).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03746", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2606.01286", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution (2606.01286).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01286", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.05160", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors (2606.05160).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.05160", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2606.05158", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Streaming Communication in Multi-Agent Reasoning", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Streaming Communication in Multi-Agent Reasoning (2606.05158).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.05158", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.05121", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Audio Interaction Model", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Audio Interaction Model (2606.05121).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.05121", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.05008", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks (2606.05008).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.05008", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.04036", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Self-Distilled Policy Gradient", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Self-Distilled Policy Gradient (2606.04036).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.04036", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.03197", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemTrain: Self-Supervised Context Memory Training", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for MemTrain: Self-Supervised Context Memory Training (2606.03197).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03197", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01166", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BraveGuard: From Open-World Threats to Safer Computer-Use Agents", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for BraveGuard: From Open-World Threats to Safer Computer-Use Agents (2606.01166).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01166", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.04688", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MeshWeaver: Sparse-Voxel-Guided Surface Weaving for Autoregressive Mesh Generation", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for MeshWeaver: Sparse-Voxel-Guided Surface Weaving for Autoregressive Mesh Generation (2606.04688).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.04688", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00377", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Score-Control for Hallucination Reduction in Diffusion Models", "date": "2026-06-04", "createdAt": "2026-06-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Score-Control for Hallucination Reduction in Diffusion Models (2606.00377).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00377", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2606.00683", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OCC-RAG: Optimal Cognitive Core for Faithful Question Answering", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Compact task-specialized language models demonstrate superior performance in multi-hop reasoning and faithfulness compared to larger general-purpose models through a novel training pipeline and structured reasoning traces. Recent progress in the development...", "popularity": {"value": 73, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.00683", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.23895", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Activation to Causality: Discovery of Causal Visual Representations in the Human Brain", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "BrainCause framework uses generative and brain models to identify valid neural representations through causal testing, demonstrating that activation alone is insufficient for confirming concept representation. Identifying which brain regions represent a vis...", "popularity": {"value": 42, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23895", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2606.01249", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Trust Region On-Policy Distillation", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Trust Region On-Policy Distillation (TrOPD) improves reliable token-level supervision in large language model distillation by using trust regions, outlier estimation, and off-policy guidance to address instability issues under distribution mismatch. On-Poli...", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01249", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03985", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Humanoid-GPT is a GPT-style Transformer with causal attention trained on a billion-scale motion corpus that achieves zero-shot generalization to unseen motions and control tasks through scalable pre-training on diverse motion data. We introduce Humanoid-GPT...", "popularity": {"value": 32, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03985", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.03458", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "KVarN is a calibration-free KV-cache quantizer that uses Hadamard rotation and dual-scaling variance normalization to reduce error accumulation during autoregressive decoding in large language models. Test-time scaling is a powerful approach to obtain bette...", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03458", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2606.02398", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Local Perturbation Theory for Cross-Domain Interference and Recovery in Multi-Domain RL", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Multi-domain reinforcement learning in language models causes performance degradation through shared computational pathways, but targeted refresh and rollback techniques can selectively recover lost capabilities with minimal side effects. Reinforcement lear...", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02398", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2606.03603", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Controlled concrete reasoning combines visual simulation with abstract reasoning through a training method that uses privileged future information to improve prediction accuracy and robustness. World models and multimodal large language models (MLLMs) provi...", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03603", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01961", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoMedBench: Towards Medical AutoResearch with Agentic AI Models", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AutoMedBench presents a comprehensive benchmark for autonomous medical-AI research that evaluates agent performance across five workflow stages, revealing validation as the weakest stage and highlighting the importance of reliable pipeline execution and ver...", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01961", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30288", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "MIRA is a source-aware filtering framework for mid-training data selection in LLM development that uses self-anchored rubric discovery to balance scalability and semantic accuracy across heterogeneous data sources. Mid-training has become an important stage...", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30288", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03979", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Deep learning models with sleep and dreaming paradigms enable continual learning through memory consolidation and self-improvement phases. The past few decades have witnessed significant advances in the design of machine learning algorithms, from early stud...", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03979", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2606.03920", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Benchmarking Visual State Tracking in Multimodal Video Understanding", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Current multimodal large language models struggle with visual state tracking in videos, performing poorly even when human-level capabilities are required, and existing agentic approaches do not effectively address these limitations. Understanding a video re...", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03920", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01599", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TRON: Targeted Rule-Verifiable Online Environments for Visual Reasoning RL", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "TRON enables scalable and controllable reinforcement learning for visual reasoning through an online environment substrate that generates unlimited diverse training instances with verifiable answers. Reinforcement learning (RL) for visual reasoning needs sc...", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01599", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03159", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OmniDreams, a foundation generative world model trained from the Cosmos diffusion model, enables real-time action-conditioned video generation for autonomous driving policy evaluation in complex, unseen scenarios. As autonomous vehicle capabilities advance,...", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03159", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01717", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Instruction tuning of large language models can be improved through decentralized training that partitions mixed datasets based on gradient conflicts and merges results via weighted averaging, achieving performance comparable to centralized methods with red...", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01717", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2606.03911", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Bootstrap Your Generator: Unpaired Visual Editing with Flow Matching", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Bootstrap Your Generator framework enables unpaired training of flow matching editing models by leveraging base model knowledge and gradient routing for improved generalization in data-scarce scenarios. Modern generative models possess a deep understanding...", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03911", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.30039", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning (2605.30039).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30039", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02754", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Ψ-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Ψ-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues (2606.02754).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02754", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01048", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Decoupled Residual Denoising Diffusion Models for Unified and Data Efficient Image-to-Image Translation", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Decoupled Residual Denoising Diffusion Models for Unified and Data Efficient Image-to-Image Translation (2606.01048).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01048", "tags": ["huggingface-papers", "image-generation", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2606.03102", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling (2606.03102).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03102", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01770", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams (2606.01770).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01770", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03264", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training (2606.03264).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03264", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01788", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PlatonicNav: Unveiling Semantic Correspondence in Navigation with Platonic Topological Maps", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for PlatonicNav: Unveiling Semantic Correspondence in Navigation with Platonic Topological Maps (2606.01788).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01788", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29288", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Diagnosing Harmful Continuation in Answer-Correct Long-CoT Training Traces", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Diagnosing Harmful Continuation in Answer-Correct Long-CoT Training Traces (2605.29288).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29288", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.03928", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Value-Aware Stochastic KV Cache Eviction for Reasoning Models", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Value-Aware Stochastic KV Cache Eviction for Reasoning Models (2606.03928).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03928", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2606.01476", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniOPD: Logit-Free On-Policy Distillation via Speculative Verification", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for OmniOPD: Logit-Free On-Policy Distillation via Speculative Verification (2606.01476).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01476", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27346", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MERIT: Learning Disentangled Music Representations for Audio Similarity", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for MERIT: Learning Disentangled Music Representations for Audio Similarity (2605.27346).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27346", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.03748", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models (2606.03748).", "popularity": {"value": 4, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03748", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2606.03029", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Conditional Hypothesis Generation for LLM-Based Text Analysis with Researcher-Specified Covariates", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Conditional Hypothesis Generation for LLM-Based Text Analysis with Researcher-Specified Covariates (2606.03029).", "popularity": {"value": 4, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03029", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00138", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Multi-AI-agent Framework Enabling End-to-end Finite Element Analysis for Solid Mechanics Problems", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for A Multi-AI-agent Framework Enabling End-to-end Finite Element Analysis for Solid Mechanics Problems (2606.00138).", "popularity": {"value": 4, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.00138", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01494", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree (2606.01494).", "popularity": {"value": 3, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01494", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00386", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "αDepth: Learning Single-Pass Soft Boundary Decomposition for Stereo Conversion", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for αDepth: Learning Single-Pass Soft Boundary Decomposition for Stereo Conversion (2606.00386).", "popularity": {"value": 3, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.00386", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.04433", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stateful Visual Encoders for Vision-Language Models", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Stateful Visual Encoders for Vision-Language Models (2606.04433).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.04433", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2606.02775", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AURA: Action-Gated Memory for Robot Policies at Constant VRAM", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for AURA: Action-Gated Memory for Robot Policies at Constant VRAM (2606.02775).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02775", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30581", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Prior Availability in Industrial Visual Sim-to-Real: A Review of CAD-Guided and CAD-Unavailable Regimes", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Prior Availability in Industrial Visual Sim-to-Real: A Review of CAD-Guided and CAD-Unavailable Regimes (2605.30581).", "popularity": {"value": 2, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30581", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.04455", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development? (2606.04455).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.04455", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03348", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SynCred-Bench: Benchmarking Synthetic Credibility in AI-Generated Visual Misinformation", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for SynCred-Bench: Benchmarking Synthetic Credibility in AI-Generated Visual Misinformation (2606.03348).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03348", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.03287", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BA-T: An Iterative Transformer for Two-View Bundle Adjustment", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for BA-T: An Iterative Transformer for Two-View Bundle Adjustment (2606.03287).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.03287", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02578", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling (2606.02578).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02578", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2606.02461", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents (2606.02461).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02461", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27958", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations (2605.27958).", "popularity": {"value": 1, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27958", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.04889", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GRAIL: Gradient-Reweighted Advantages for Reinforcement Learning with Verifiable Rewards", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for GRAIL: Gradient-Reweighted Advantages for Reinforcement Learning with Verifiable Rewards (2606.04889).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.04889", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01955", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WALL-WM: Carving World Action Modeling at the Event Joints", "date": "2026-06-03", "createdAt": "2026-06-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face daily paper entry for WALL-WM: Carving World Action Modeling at the Event Joints (2606.01955).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.01955", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30611", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs (2605.30611).", "popularity": {"value": 112, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30611", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.02437", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters (2606.02437).", "popularity": {"value": 86, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02437", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28556", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Matter of TASTE: Improving Coverage and Difficulty of Agent Benchmarks", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Matter of TASTE: Improving Coverage and Difficulty of Agent Benchmarks (2605.28556).", "popularity": {"value": 55, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28556", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29707", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Domino: Decoupling Causal Modeling from Autoregressive Drafting in Speculative Decoding", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Domino: Decoupling Causal Modeling from Autoregressive Drafting in Speculative Decoding (2605.29707).", "popularity": {"value": 52, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29707", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02404", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts (2606.02404).", "popularity": {"value": 47, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02404", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.00408", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Masking Stale Observations Helps Search Agents -- Until It Doesn't: A Regime Map and Its Mechanism", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Masking Stale Observations Helps Search Agents -- Until It Doesn't: A Regime Map and Its Mechanism (2606.00408).", "popularity": {"value": 43, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.00408", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.02373", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses (2606.02373).", "popularity": {"value": 34, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02373", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29343", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Draft-OPD: On-Policy Distillation for Speculative Draft Models", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Draft-OPD: On-Policy Distillation for Speculative Draft Models (2605.29343).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29343", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24956", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NITP: Next Implicit Token Prediction for LLM Pre-training", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for NITP: Next Implicit Token Prediction for LLM Pre-training (2605.24956).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24956", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30501", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs (2605.30501).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30501", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2606.02482", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding (2606.02482).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02482", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02564", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization (2606.02564).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02564", "tags": ["huggingface-papers", "multimodal", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30351", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VideoMLA: Low-Rank Latent KV Cache for Minute-Scale Autoregressive Video Diffusion", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VideoMLA: Low-Rank Latent KV Cache for Minute-Scale Autoregressive Video Diffusion (2605.30351).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30351", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2606.01247", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration?", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration? (2606.01247).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01247", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.01311", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories (2606.01311).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01311", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28132", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models (2605.28132).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28132", "tags": ["huggingface-papers", "multimodal", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.29860", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ESPO: Early-Stopping Proximal Policy Optimization", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ESPO: Early-Stopping Proximal Policy Optimization (2605.29860).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29860", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02470", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation (2606.02470).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02470", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24202", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs (2605.24202).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24202", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31057", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LVSA: Training-Free Sparse Attention for Long Video Diffusion", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LVSA: Training-Free Sparse Attention for Long Video Diffusion (2605.31057).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31057", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2606.02553", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongLive-RAG: A General Retrieval-Augmented Framework for Long Video Generation", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LongLive-RAG: A General Retrieval-Augmented Framework for Long Video Generation (2606.02553).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02553", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2606.01528", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Joint Agent Memory and Exploration Learning via Novelty Signals", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Joint Agent Memory and Exploration Learning via Novelty Signals (2606.01528).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01528", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29588", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Brain-IT-VQA: From Brain Signals to Answers", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Brain-IT-VQA: From Brain Signals to Answers (2605.29588).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29588", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25659", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StreamChar: Long-Horizon Streaming Character Audio-Video Generation with Decoupled Orchestration", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StreamChar: Long-Horizon Streaming Character Audio-Video Generation with Decoupled Orchestration (2605.25659).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25659", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2606.02031", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents (2606.02031).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02031", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30723", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Skill is Not One-Size-Fits-All: Model-Aware Skill Alignment for LLM Agents", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Skill is Not One-Size-Fits-All: Model-Aware Skill Alignment for LLM Agents (2605.30723).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30723", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.02388", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Policy and World Modeling Co-Training for Language Agents", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Policy and World Modeling Co-Training for Language Agents (2606.02388).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02388", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30852", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism (2605.30852).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30852", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30931", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft (2605.30931).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30931", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.02551", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AFUN: Towards an Affordance Foundation Model for Functionality Understanding", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AFUN: Towards an Affordance Foundation Model for Functionality Understanding (2606.02551).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02551", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01414", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agent Skills Should Go Beyond Text: The Case for Visual Skills", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agent Skills Should Go Beyond Text: The Case for Visual Skills (2606.01414).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01414", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.00828", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes (2606.00828).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.00828", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30126", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding (2605.30126).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30126", "tags": ["huggingface-papers", "multimodal", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2606.02277", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RoboSemanticBench: Diagnosing Semantic Grounding in Action Prediction for VLA Models", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RoboSemanticBench: Diagnosing Semantic Grounding in Action Prediction for VLA Models (2606.02277).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.02277", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01682", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Off-the-Shelf LLMs as Process Scorers: Training-Free Alternative to PRMs for Mathematical Reasoning", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Off-the-Shelf LLMs as Process Scorers: Training-Free Alternative to PRMs for Mathematical Reasoning (2606.01682).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01682", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01533", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Multi-Agent Computer Use", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Multi-Agent Computer Use (2606.01533).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2606.01533", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31597", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SOCO: Benchmarking Semantic Object Correspondence in Vision Foundation Models", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SOCO: Benchmarking Semantic Object Correspondence in Vision Foundation Models (2605.31597).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31597", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24614", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Measuring the Depth of LLM Unlearning via Activation Patching", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Measuring the Depth of LLM Unlearning via Activation Patching (2605.24614).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24614", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02580", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models (2606.02580).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.02580", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2606.02320", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TVIR: Building Deep Research Agents Towards Text--Visual Interleaved Report Generation", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for TVIR: Building Deep Research Agents Towards Text--Visual Interleaved Report Generation (2606.02320).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.02320", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.02255", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025 (2606.02255).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.02255", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.02248", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometric Latent Reasoning Induces Shorter Generations in LLMs", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Geometric Latent Reasoning Induces Shorter Generations in LLMs (2606.02248).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.02248", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.01666", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DOT-MoE: Differentiable Optimal Transport for MoEfication", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for DOT-MoE: Differentiable Optimal Transport for MoEfication (2606.01666).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.01666", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2606.01027", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "τ_0-WM: A Unified Video-Action World Model for Robotic Manipulation", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for τ_0-WM: A Unified Video-Action World Model for Robotic Manipulation (2606.01027).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.01027", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2606.00761", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Confidence-Adaptive SwiGLU for Mixture-of-Experts", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Confidence-Adaptive SwiGLU for Mixture-of-Experts (2606.00761).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00761", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00660", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search (2606.00660).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00660", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.00285", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Model-Based Quality Assessment for Massively Multilingual Parallel Data", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Model-Based Quality Assessment for Massively Multilingual Parallel Data (2606.00285).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00285", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00267", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement (2606.00267).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00267", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2606.00240", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MindZero: Learning Online Mental Reasoning With Zero Annotations", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for MindZero: Learning Online Mental Reasoning With Zero Annotations (2606.00240).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00240", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00090", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Silent Failures in Physical AI: A Literature Review of Runtime Action Authorization for Autonomous Systems", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Silent Failures in Physical AI: A Literature Review of Runtime Action Authorization for Autonomous Systems (2606.00090).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00090", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2606.00089", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Can Predicted Dynamics Exist in the Physical World?", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Can Predicted Dynamics Exist in the Physical World? (2606.00089).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2606.00089", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.31529", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SVI-Bench: A Dynamic Microworld for Strategic Video Intelligence", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for SVI-Bench: A Dynamic Microworld for Strategic Video Intelligence (2605.31529).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.31529", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30608", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Semantic Motion Anchors: Bridging Motion and Meaning in Co-Speech Gestures", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Semantic Motion Anchors: Bridging Motion and Meaning in Co-Speech Gestures (2605.30608).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30608", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29992", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation (2605.29992).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29992", "tags": ["embeddings", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29318", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FreeForm: Reduced-Order Deformable Simulation from Particle-Based Skinning Eigenmodes", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for FreeForm: Reduced-Order Deformable Simulation from Particle-Based Skinning Eigenmodes (2605.29318).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29318", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29087", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure (2605.29087).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29087", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29084", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG (2605.29084).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29084", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.28983", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Hamilton-Jacobi Theory of Deep Learning", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for The Hamilton-Jacobi Theory of Deep Learning (2605.28983).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28983", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2605.28615", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization (2605.28615).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28615", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28255", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering? (2605.28255).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28255", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27921", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Show, Don't TELL: Explainable AI-Generated Text Detection", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Show, Don't TELL: Explainable AI-Generated Text Detection (2605.27921).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27921", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26248", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Unified Neural Scaling Laws", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Unified Neural Scaling Laws (2605.26248).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26248", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25381", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Not only where, But when: Temporal Scheduling for RLVR", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for Not only where, But when: Temporal Scheduling for RLVR (2605.25381).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.25381", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21102", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ACL-Verbatim: hallucination-free question answering for research", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for ACL-Verbatim: hallucination-free question answering for research (2605.21102).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21102", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16745", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers", "date": "2026-06-02", "createdAt": "2026-06-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T03:04:34+00:00", "summary": "Hugging Face daily paper entry for EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers (2605.16745).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.16745", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2605.30993", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SwanVoice: Expressive Long-Form Zero-Shot Speech Synthesis for Both Monologue and Dialogue", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SwanVoice: Expressive Long-Form Zero-Shot Speech Synthesis for Both Monologue and Dialogue (2605.30993).", "popularity": {"value": 50, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30993", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.31268", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mellum2 Technical Report", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mellum2 Technical Report (2605.31268).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31268", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.31584", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongTraceRL: Learning Long-Context Reasoning from Search Agent Trajectories with Rubric Rewards", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LongTraceRL: Learning Long-Context Reasoning from Search Agent Trajectories with Rubric Rewards (2605.31584).", "popularity": {"value": 38, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31584", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31039", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration (2605.31039).", "popularity": {"value": 36, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31039", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.30819", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Function2Scene: 3D Indoor Scene Layout from Functional Specifications", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Function2Scene: 3D Indoor Scene Layout from Functional Specifications (2605.30819).", "popularity": {"value": 36, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30819", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30409", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer (2605.30409).", "popularity": {"value": 32, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30409", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30940", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer (2605.30940).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30940", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.31075", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Task-Focused Memorization for Multimodal Agents", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Task-Focused Memorization for Multimodal Agents (2605.31075).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31075", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30876", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "dMoE: dLLMs with Learnable Block Experts", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for dMoE: dLLMs with Learnable Block Experts (2605.30876).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30876", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28618", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios (2605.28618).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28618", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31433", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks (2605.31433).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31433", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26844", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Not All Disagreement Is Learnable: Token Teachability in On-Policy Distillation", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Not All Disagreement Is Learnable: Token Teachability in On-Policy Distillation (2605.26844).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26844", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29796", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SAAS: Self-Aware Reinforcement Learning for Over-Search Mitigation in Agentic Search", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SAAS: Self-Aware Reinforcement Learning for Over-Search Mitigation in Agentic Search (2605.29796).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29796", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30407", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Exploring Autonomous Agentic Data Engineering for Model Specialization", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Exploring Autonomous Agentic Data Engineering for Model Specialization (2605.30407).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30407", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31029", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PEEK: Picking Essential frames via Efficient Knowledge distillation", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PEEK: Picking Essential frames via Efficient Knowledge distillation (2605.31029).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31029", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.30561", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VLM3: Vision Language Models Are Native 3D Learners", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VLM3: Vision Language Models Are Native 3D Learners (2605.30561).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30561", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.30434", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis (2605.30434).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30434", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29447", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents (2605.29447).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29447", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30621", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents (2605.30621).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30621", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02772", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Linearizing Vision Transformer with Test-Time Training", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Linearizing Vision Transformer with Test-Time Training (2605.02772).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02772", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.31042", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors (2605.31042).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31042", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31598", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Linear Scaling Video VLMs for Long Video Understanding", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Linear Scaling Video VLMs for Long Video Understanding (2605.31598).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31598", "tags": ["huggingface-papers", "multimodal", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.31336", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DecMem: Towards Minute-Long Consistent World Generation with Decoupled Memory", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DecMem: Towards Minute-Long Consistent World Generation with Decoupled Memory (2605.31336).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31336", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28657", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DEMON: Diffusion Engine for Musical Orchestrated Noise", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DEMON: Diffusion Engine for Musical Orchestrated Noise (2605.28657).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28657", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.30011", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies (2605.30011).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30011", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.17543", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos (2605.17543).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17543", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30846", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Count Anything", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Count Anything (2605.30846).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30846", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30834", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring (2605.30834).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30834", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30557", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)?", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)? (2605.30557).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30557", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.31503", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "How can embedding models bind concepts?", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for How can embedding models bind concepts? (2605.31503).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31503", "tags": ["embeddings", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30888", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement (2605.30888).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30888", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30329", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones?", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? (2605.30329).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30329", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.31603", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models (2605.31603).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31603", "tags": ["huggingface-papers", "paper", "research", "small-local", "video-generation"]}
{"id": "paper:arxiv:2605.31535", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video (2605.31535).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31535", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.31170", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Emergent Languages in Populations of Language Model Agents: From Token Efficiency to Oversight Evasion", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Emergent Languages in Populations of Language Model Agents: From Token Efficiency to Oversight Evasion (2605.31170).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.31170", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30514", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MAAT: Multi-phase Adapter-Aware Targeted Unlearning", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MAAT: Multi-phase Adapter-Aware Targeted Unlearning (2605.30514).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30514", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29429", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation (2605.29429).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29429", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.28992", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FRAPPE: Full Input, Residual Output Autoencoding with Projection Pursuit Encoder", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FRAPPE: Full Input, Residual Output Autoencoding with Projection Pursuit Encoder (2605.28992).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28992", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26112", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Model Scaling to System Scaling: Scaling the Harness in Agentic AI", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Model Scaling to System Scaling: Scaling the Harness in Agentic AI (2605.26112).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26112", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23657", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents (2605.23657).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23657", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23458", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "One-Forcing: Towards Stable One-Step Autoregressive Video Generation", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for One-Forcing: Towards Stable One-Step Autoregressive Video Generation (2605.23458).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23458", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.31577", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SurGe: Improved Surface Geometry in Point Maps", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for SurGe: Improved Surface Geometry in Point Maps (2605.31577).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.31577", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.31455", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization (2605.31455).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.31455", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.31158", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models (2605.31158).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.31158", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.31096", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning (2605.31096).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.31096", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30571", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode (2605.30571).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30571", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.29488", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling (2605.29488).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29488", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29411", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction (2605.29411).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29411", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29398", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models (2605.29398).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29398", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.29198", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Guidance Contrastive Token Credit Assignment for Discrete Policy Optimization", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Guidance Contrastive Token Credit Assignment for Discrete Policy Optimization (2605.29198).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29198", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28969", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Recall: Behavioral Specification as an Interpretive Layer for AI Personalization", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Beyond Recall: Behavioral Specification as an Interpretive Layer for AI Personalization (2605.28969).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28969", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28730", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AlphaTransit: Learning to Design City-scale Transit Routes", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for AlphaTransit: Learning to Design City-scale Transit Routes (2605.28730).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28730", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28181", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When Confidence Misleads: Suffix Anchoring and Anchor-Proximity Confidence Modulation for Diffusion Language Models", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for When Confidence Misleads: Suffix Anchoring and Anchor-Proximity Confidence Modulation for Diffusion Language Models (2605.28181).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28181", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.27919", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal (2605.27919).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27919", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.26562", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting (2605.26562).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26562", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24442", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Benchmarking Composed Image Retrieval for Applied Earth Observation", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Benchmarking Composed Image Retrieval for Applied Earth Observation (2605.24442).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.24442", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.21625", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Flat-Pack Bench: Evaluating Spatio-Temporal Understanding in Large Vision-Language Models through Furniture Assembly", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for Flat-Pack Bench: Evaluating Spatio-Temporal Understanding in Large Vision-Language Models through Furniture Assembly (2605.21625).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21625", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15779", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Topology-Aware Spatiotemporal Handover Framework for Continuous Multi-UAV Tracking", "date": "2026-06-01", "createdAt": "2026-06-01", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face daily paper entry for A Topology-Aware Spatiotemporal Handover Framework for Continuous Multi-UAV Tracking (2605.15779).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15779", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29801", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security (2605.29801).", "popularity": {"value": 137, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29801", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30280", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments (2605.30280).", "popularity": {"value": 129, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30280", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.29250", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources (2605.29250).", "popularity": {"value": 73, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29250", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.30161", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Why Far Looks Up: Probing Spatial Representation in Vision-Language Models", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Why Far Looks Up: Probing Spatial Representation in Vision-Language Models (2605.30161).", "popularity": {"value": 57, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30161", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.25378", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation (2605.25378).", "popularity": {"value": 57, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25378", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30263", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models (2605.30263).", "popularity": {"value": 53, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30263", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30346", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "YoCausal: How Far is Video Generation from World Model? A Causality Perspective", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for YoCausal: How Far is Video Generation from World Model? A Causality Perspective (2605.30346).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30346", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30260", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "How LoRA Remembers? A Parametric Memory Law for LLM Finetuning", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for How LoRA Remembers? A Parametric Memory Law for LLM Finetuning (2605.30260).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30260", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30248", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GenClaw: Code-Driven Agentic Image Generation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GenClaw: Code-Driven Agentic Image Generation (2605.30248).", "popularity": {"value": 34, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30248", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30010", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EarlyTom: Early Token Compression Completes Fast Video Understanding", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EarlyTom: Early Token Compression Completes Fast Video Understanding (2605.30010).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30010", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30073", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Native Audio-Visual Alignment for Generation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Native Audio-Visual Alignment for Generation (2605.30073).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30073", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.28424", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning (2605.28424).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28424", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29888", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training (2605.29888).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29888", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30076", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniSteer: Text-Guided Flow Matching in Activation Space for Versatile LLM Steering", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UniSteer: Text-Guided Flow Matching in Activation Space for Versatile LLM Steering (2605.30076).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30076", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30332", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Colored Noise Diffusion Sampling", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Colored Noise Diffusion Sampling (2605.30332).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30332", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.30219", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When Should Models Change Their Minds? Contextual Belief Management in Large Language Models", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When Should Models Change Their Minds? Contextual Belief Management in Large Language Models (2605.30219).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30219", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30265", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LoMo: Local Modality Substitution for Deeper Vision-Language Fusion", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LoMo: Local Modality Substitution for Deeper Vision-Language Fusion (2605.30265).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30265", "tags": ["huggingface-papers", "multimodal", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.29507", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Xetrieval: Mechanistically Explaining Dense Retrieval", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Xetrieval: Mechanistically Explaining Dense Retrieval (2605.29507).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29507", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.26578", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Is Position Bias in Dense Retrievers Built In-or Learned from Data?", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Is Position Bias in Dense Retrievers Built In-or Learned from Data? (2605.26578).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26578", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.26029", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists (2605.26029).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26029", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29559", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents (2605.29559).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29559", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29341", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction (2605.29341).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29341", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27995", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios (2605.27995).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27995", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30102", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems (2605.30102).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30102", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26730", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PRISM: A Multi-Dimensional Benchmark for Evaluating LLM Peer Reviewers", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PRISM: A Multi-Dimensional Benchmark for Evaluating LLM Peer Reviewers (2605.26730).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26730", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29861", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation (2605.29861).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29861", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.29534", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UI-KOBE: Knowledge-Oriented Behavior Exploration for Lightweight Graph-Guided GUI Agents", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UI-KOBE: Knowledge-Oriented Behavior Exploration for Lightweight Graph-Guided GUI Agents (2605.29534).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29534", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30349", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AdaState: Self-Evolving Anchors for Streaming Video Generation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AdaState: Self-Evolving Anchors for Streaming Video Generation (2605.30349).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30349", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30093", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometry Matters: 3D Foundation Priors for Learning Semantic Correspondence", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geometry Matters: 3D Foundation Priors for Learning Semantic Correspondence (2605.30093).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30093", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29156", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains (2605.29156).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29156", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30350", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation (2605.30350).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30350", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30347", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NeuROK: Generative 4D Neural Object Kinematics", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for NeuROK: Generative 4D Neural Object Kinematics (2605.30347).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30347", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30268", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhyGenHOI: Physically-Aware 4D Generation of Dynamic Human-Object Interactions", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhyGenHOI: Physically-Aware 4D Generation of Dynamic Human-Object Interactions (2605.30268).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30268", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29157", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Parallax: Parameterized Local Linear Attention for Language Modeling", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Parallax: Parameterized Local Linear Attention for Language Modeling (2605.29157).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29157", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.24785", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PANDO: Efficient Multimodal AI Agents via Online Skill Distillation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PANDO: Efficient Multimodal AI Agents via Online Skill Distillation (2605.24785).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24785", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30052", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "REPOT: Recoverable Program-of-Thought via Checkpoint Repair", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for REPOT: Recoverable Program-of-Thought via Checkpoint Repair (2605.30052).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30052", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29648", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering (2605.29648).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29648", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.29548", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention (2605.29548).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29548", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2601.07525", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Thinking Before Constraining: A Unified Decoding Framework for Large Language Models", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Thinking Before Constraining: A Unified Decoding Framework for Large Language Models (2601.07525).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2601.07525", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29271", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval (2605.29271).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29271", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.21781", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reflective Prompt Tuning through Language Model Function-Calling", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Reflective Prompt Tuning through Language Model Function-Calling (2605.21781).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21781", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29257", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ChildVox: A Speech, Audio, and Large Audio-Language Model Benchmark in Understanding and Characterizing Sound across Childhood", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ChildVox: A Speech, Audio, and Large Audio-Language Model Benchmark in Understanding and Characterizing Sound across Childhood (2605.29257).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.29257", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27891", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SmartDirector: Keyframe-Conditioned Cinematic Video Generation with Narrative Pacing Control", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SmartDirector: Keyframe-Conditioned Cinematic Video Generation with Narrative Pacing Control (2605.27891).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27891", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.24786", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CONF-KV: Confidence-Aware KV Cache Eviction with Mixed-Precision Storage for Long-Horizon LLM", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CONF-KV: Confidence-Aware KV Cache Eviction with Mixed-Precision Storage for Long-Horizon LLM (2605.24786).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24786", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.22189", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments (2605.22189).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22189", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.30189", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Token-Level Generalization in LoRA Adapter Backdoors: Attack Characterization and Behavioral Detection", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Token-Level Generalization in LoRA Adapter Backdoors: Attack Characterization and Behavioral Detection (2605.30189).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.30189", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27355", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases (2605.27355).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27355", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25220", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation (2605.25220).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25220", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23235", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Convex Low-resource Accent-Robust Language Detection in Speech Recognition", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Convex Low-resource Accent-Robust Language Detection in Speech Recognition (2605.23235).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23235", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.30344", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection (2605.30344).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30344", "tags": ["huggingface-papers", "multimodal", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.30231", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond 3D VQAs: Injecting 3D Spatial Priors into Vision-Language Models for Enhanced Geometric Reasoning", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Beyond 3D VQAs: Injecting 3D Spatial Priors into Vision-Language Models for Enhanced Geometric Reasoning (2605.30231).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30231", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.30060", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Consistent Video Geometry Estimation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Towards Consistent Video Geometry Estimation (2605.30060).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30060", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.30003", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas (2605.30003).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.30003", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.29486", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhoneWorld: Scaling Phone-Use Agent Environments", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for PhoneWorld: Scaling Phone-Use Agent Environments (2605.29486).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.29486", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26485", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistants", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistants (2605.26485).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26485", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22771", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reducing Political Manipulation with Consistency Training", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Reducing Political Manipulation with Consistency Training (2605.22771).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22771", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22765", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation (2605.22765).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22765", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.16363", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage (2605.16363).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.16363", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13857", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation", "date": "2026-05-31", "createdAt": "2026-05-31", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation (2605.13857).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.13857", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.28816", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "A generative multi-agent world model is presented that uses simplex rotary agent encoding and sparse hub attention to enable scalable, permutation-symmetric interaction between multiple agents in interactive video generation. World models for interactive vi...", "popularity": {"value": 417, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28816", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28774", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agent Explorative Policy Optimization for Multimodal Agentic Reasoning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agent Explorative Policy Optimization for Multimodal Agentic Reasoning (2605.28774).", "popularity": {"value": 86, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28774", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28293", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation (2605.28293).", "popularity": {"value": 85, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28293", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28820", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Pixels to Words -- Towards Native One-Vision Models at Scale", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Pixels to Words -- Towards Native One-Vision Models at Scale (2605.28820).", "popularity": {"value": 70, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28820", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.28814", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Self-Improving Language Models with Bidirectional Evolutionary Search", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Self-Improving Language Models with Bidirectional Evolutionary Search (2605.28814).", "popularity": {"value": 56, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28814", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28003", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ResearchMath-14K: Scaling Research-Level Mathematics via Agents", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ResearchMath-14K: Scaling Research-Level Mathematics via Agents (2605.28003).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28003", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28421", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DenoiseRL: Bootstrapping Reasoning Models to Recover from Noisy Prefixes", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DenoiseRL: Bootstrapping Reasoning Models to Recover from Noisy Prefixes (2605.28421).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28421", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28548", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GEM: Generative Supervision Helps Embodied Intelligence", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GEM: Generative Supervision Helps Embodied Intelligence (2605.28548).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28548", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.28732", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems (2605.28732).", "popularity": {"value": 39, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28732", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28775", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents (2605.28775).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28775", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26340", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence (2605.26340).", "popularity": {"value": 35, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26340", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28773", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking Memory as Continuously Evolving Connectivity", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking Memory as Continuously Evolving Connectivity (2605.28773).", "popularity": {"value": 32, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28773", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26302", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems (2605.26302).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26302", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27760", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillGrad: Optimizing Agent Skills Like Gradient Descent", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkillGrad: Optimizing Agent Skills Like Gradient Descent (2605.27760).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27760", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27905", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AI Research Agents Narrow Scientific Exploration", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AI Research Agents Narrow Scientific Exploration (2605.27905).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27905", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28691", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning (2605.28691).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28691", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.28534", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GUI-CIDER: Mid-training GUI Agents via Causal Internalization and Density-aware Exemplar Reselection", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GUI-CIDER: Mid-training GUI Agents via Causal Internalization and Density-aware Exemplar Reselection (2605.28534).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28534", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28109", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization (2605.28109).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28109", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25969", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Triplet-Block Diffusion RWKV", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Triplet-Block Diffusion RWKV (2605.25969).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25969", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.27310", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning (2605.27310).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27310", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.26396", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Advancing Creative Physical Intelligence in Large Multimodal Models", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Advancing Creative Physical Intelligence in Large Multimodal Models (2605.26396).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26396", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.27491", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation (2605.27491).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27491", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.23163", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving (2605.23163).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23163", "tags": ["huggingface-papers", "image-generation", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.28721", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LiveBrowseComp: Are Search Agents Searching, or Just Verifying What They Already Know?", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LiveBrowseComp: Are Search Agents Searching, or Just Verifying What They Already Know? (2605.28721).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28721", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28398", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HRBench: Benchmarking and Understanding Thinking-Mode Switch Strategies in Hybrid-Reasoning LLMs", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HRBench: Benchmarking and Understanding Thinking-Mode Switch Strategies in Hybrid-Reasoning LLMs (2605.28398).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28398", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27354", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders (2605.27354).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27354", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28763", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CubePart: An Open-Vocabulary Part-Controllable 3D Generator", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CubePart: An Open-Vocabulary Part-Controllable 3D Generator (2605.28763).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28763", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27882", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VibeSearchBench: Benchmarking Long-horizon Proactive Search in the Wild", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VibeSearchBench: Benchmarking Long-horizon Proactive Search in the Wild (2605.27882).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27882", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27268", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lost in Sampling: Assessing Lexical Reachability in LLMs via the Word Coverage Score (WCS)", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Lost in Sampling: Assessing Lexical Reachability in LLMs via the Word Coverage Score (WCS) (2605.27268).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27268", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.27028", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Less is More: Early Stopping Rollout for On-Policy Distillation", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Less is More: Early Stopping Rollout for On-Policy Distillation (2605.27028).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27028", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26032", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution (2605.26032).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26032", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.27901", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Fragility of Chain-of-Thought Monitoring Across Typologically Diverse Languages", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Fragility of Chain-of-Thought Monitoring Across Typologically Diverse Languages (2605.27901).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27901", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.26574", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GradSentry: Gradient Spectral Entropy for Backdoor Sample Filtering in Large Language Model Fine-Tuning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GradSentry: Gradient Spectral Entropy for Backdoor Sample Filtering in Large Language Model Fine-Tuning (2605.26574).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26574", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28805", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration (2605.28805).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28805", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.28655", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation (2605.28655).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28655", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19952", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent Memory", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent Memory (2605.19952).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19952", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28819", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective (2605.28819).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28819", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28591", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Models That Know How Evaluations Are Designed Score Safer", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Models That Know How Evaluations Are Designed Score Safer (2605.28591).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28591", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28257", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Category-Level 3D Correspondence in Camera Space via Morphable Object Priors", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Category-Level 3D Correspondence in Camera Space via Morphable Object Priors (2605.28257).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28257", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27466", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems (2605.27466).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27466", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28617", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LACUNA: Safe Agents as Recursive Program Holes", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LACUNA: Safe Agents as Recursive Program Holes (2605.28617).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28617", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27762", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft (2605.27762).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27762", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28184", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration (2605.28184).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28184", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.28158", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OR-Space: A Full-Lifecycle Workspace Benchmark for Industrial Optimization Agents", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OR-Space: A Full-Lifecycle Workspace Benchmark for Industrial Optimization Agents (2605.28158).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28158", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27908", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ESC-Skills: Discovering and Self-Evolving Skills for Emotional Support Conversations", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ESC-Skills: Discovering and Self-Evolving Skills for Emotional Support Conversations (2605.27908).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27908", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26457", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Verus-SpecGym: An Agentic Environment for Evaluating Specification Autoformalization", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Verus-SpecGym: An Agentic Environment for Evaluating Specification Autoformalization (2605.26457).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26457", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25707", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions (2605.25707).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25707", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24486", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning (2605.24486).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24486", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.28510", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Efficient and Scalable Provenance Tracking for LLM-Generated Code Snippets", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Efficient and Scalable Provenance Tracking for LLM-Generated Code Snippets (2605.28510).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.28510", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.24053", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models (2605.24053).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24053", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.28034", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Clark Hash: Stateless Sparse Johnson-Lindenstrauss Quantization for Neural Embeddings", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Clark Hash: Stateless Sparse Johnson-Lindenstrauss Quantization for Neural Embeddings (2605.28034).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.28034", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.27824", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Revealing Algorithmic Deductive Circuits for Logical Reasoning", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Revealing Algorithmic Deductive Circuits for Logical Reasoning (2605.27824).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27824", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27766", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems (2605.27766).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27766", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27311", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models (2605.27311).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27311", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27044", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting (2605.27044).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.27044", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2605.25174", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Growing a Neural Network in Breadth, Depth, and Time", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Growing a Neural Network in Breadth, Depth, and Time (2605.25174).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.25174", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2605.17531", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Don't Guess, Just Ask: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification", "date": "2026-05-28", "createdAt": "2026-05-28", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Don't Guess, Just Ask: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification (2605.17531).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17531", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
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{"id": "paper:arxiv:2605.27365", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding (2605.27365).", "popularity": {"value": 134, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27365", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.23271", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation (2605.23271).", "popularity": {"value": 79, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23271", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27367", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SpatialBench: Is Your Spatial Foundation Model an All-Round Player?", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SpatialBench: Is Your Spatial Foundation Model an All-Round Player? (2605.27367).", "popularity": {"value": 70, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27367", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26114", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research (2605.26114).", "popularity": {"value": 62, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26114", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26230", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction (2605.26230).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26230", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26494", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence (2605.26494).", "popularity": {"value": 39, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26494", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26244", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV (2605.26244).", "popularity": {"value": 38, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26244", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25893", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "D^2-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation-Aware Routing", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for D^2-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation-Aware Routing (2605.25893).", "popularity": {"value": 38, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25893", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.17423", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration (2605.17423).", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17423", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27102", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "JLT: Clean-Latent Prediction in Latent Diffusion Transformers", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for JLT: Clean-Latent Prediction in Latent Diffusion Transformers (2605.27102).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27102", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.27030", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling (2605.27030).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27030", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.25979", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence (2605.25979).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25979", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.27366", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation (2605.27366).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27366", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27295", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini (2605.27295).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27295", "tags": ["embeddings", "huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.27068", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "QUACK: Questioning, Understanding, and Auditing Communicated Knowledge in Multimodal Social Deduction Agents", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for QUACK: Questioning, Understanding, and Auditing Communicated Knowledge in Multimodal Social Deduction Agents (2605.27068).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27068", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27476", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective (2605.27476).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27476", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.26895", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Negligible in Size, Significant in Effect: On Scale Vectors in Large Language Models", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Negligible in Size, Significant in Effect: On Scale Vectors in Large Language Models (2605.26895).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26895", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.27141", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions (2605.27141).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27141", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27209", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments (2605.27209).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27209", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26952", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement (2605.26952).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26952", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25437", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning (2605.25437).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25437", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26632", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models (2605.26632).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26632", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.25802", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking VLM Representation for VLA Initialization", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking VLM Representation for VLA Initialization (2605.25802).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25802", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.27358", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MobileMoE: Scaling On-Device Mixture of Experts", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MobileMoE: Scaling On-Device Mixture of Experts (2605.27358).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27358", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.26045", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Confidence and Calibration of Activation Oracles for Reliable Interpretation of Language Model Internals", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Confidence and Calibration of Activation Oracles for Reliable Interpretation of Language Model Internals (2605.26045).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26045", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25188", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs (2605.25188).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25188", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26111", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Squeezing Capacity from Multimodal Large Language Models for Subject-driven Generation", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Squeezing Capacity from Multimodal Large Language Models for Subject-driven Generation (2605.26111).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26111", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.24468", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SAM: State-Adaptive Memory for Long-Horizon Reasoning Agent", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SAM: State-Adaptive Memory for Long-Horizon Reasoning Agent (2605.24468).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24468", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24219", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Final Answers: Auditing Trajectory-Level Hallucinations in Multi-Agent Industrial Workflows", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond Final Answers: Auditing Trajectory-Level Hallucinations in Multi-Agent Industrial Workflows (2605.24219).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24219", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.27235", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale (2605.27235).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.27235", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.23215", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FastKernels: Benchmarking GPU Kernel Generation in Production", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FastKernels: Benchmarking GPU Kernel Generation in Production (2605.23215).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23215", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18879", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models (2605.18879).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18879", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.22608", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents (2605.22608).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22608", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26293", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CroCo: Cross-Lingual Contrastive Preference Tuning on Self-Generations", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CroCo: Cross-Lingual Contrastive Preference Tuning on Self-Generations (2605.26293).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26293", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24931", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning High-Frequency Continuous Action Chunks in Latent Space", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning High-Frequency Continuous Action Chunks in Latent Space (2605.24931).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24931", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22769", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Understanding Data Temporality Impact on Large Language Models Pre-training", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Understanding Data Temporality Impact on Large Language Models Pre-training (2605.22769).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22769", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26242", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Can LLMs Introspect? A Reality Check", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Can LLMs Introspect? A Reality Check (2605.26242).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26242", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25162", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media (2605.25162).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.25162", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15042", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration (2605.15042).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15042", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2503.08600", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NSF-SciFy: Mining the NSF Awards Database for Scientific Claims", "date": "2026-05-27", "createdAt": "2026-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for NSF-SciFy: Mining the NSF Awards Database for Scientific Claims (2503.08600).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2503.08600", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:anisoleai/fineweb-tokenized", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "anisoleai/fineweb-tokenized", "date": "2026-05-29", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63296 downloads.", "popularity": {"value": 63296, "label": "downloads"}, "url": "https://huggingface.co/datasets/anisoleai/fineweb-tokenized", "tags": ["arxiv:2406.17557", "datasets", "language:en", "license:odc-by", "modality:tabular", "modality:text", "pre-training", "region:us"]}
{"id": "paper:arxiv:2605.25604", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning (2605.25604).", "popularity": {"value": 133, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25604", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25874", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WBench: A Comprehensive Multi-turn Benchmark for Interactive Video World Model Evaluation", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WBench: A Comprehensive Multi-turn Benchmark for Interactive Video World Model Evaluation (2605.25874).", "popularity": {"value": 101, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25874", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24830", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Macaron-A2UI: A Model for Generative UI in Personal Agents", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Macaron-A2UI: A Model for Generative UI in Personal Agents (2605.24830).", "popularity": {"value": 80, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24830", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23218", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Foundation Protocol: A Coordination Layer for Agentic Society", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Foundation Protocol: A Coordination Layer for Agentic Society (2605.23218).", "popularity": {"value": 79, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23218", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26115", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TriSplat: Simulation-Ready Feed-Forward 3D Scene Reconstruction", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TriSplat: Simulation-Ready Feed-Forward 3D Scene Reconstruction (2605.26115).", "popularity": {"value": 51, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26115", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25343", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Toward Native Multimodal Modeling: A Roadmap", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Toward Native Multimodal Modeling: A Roadmap (2605.25343).", "popularity": {"value": 42, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25343", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.25535", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents (2605.25535).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25535", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24218", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks (2605.24218).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24218", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23081", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ThriftAttention: Selective Mixed Precision for Long-Context FP4 Attention", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ThriftAttention: Selective Mixed Precision for Long-Context FP4 Attention (2605.23081).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23081", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20342", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning (2605.20342).", "popularity": {"value": 34, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20342", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25624", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents (2605.25624).", "popularity": {"value": 32, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25624", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23204", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery (2605.23204).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23204", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24938", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Your Embedding Model is SMARTer Than You Think", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Your Embedding Model is SMARTer Than You Think (2605.24938).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24938", "tags": ["embeddings", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26086", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World (2605.26086).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26086", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25569", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement (2605.25569).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25569", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25449", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Pantheon360: Taming Digital Twin Generation via 3D-Aware 360° Video Diffusion", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Pantheon360: Taming Digital Twin Generation via 3D-Aware 360° Video Diffusion (2605.25449).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25449", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.24117", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills (2605.24117).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24117", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26535", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Recursive Flow Matching", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Recursive Flow Matching (2605.26535).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26535", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26105", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "On-Policy Adversarial Flow Distillation for Autoregressive Video Generation", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for On-Policy Adversarial Flow Distillation for Autoregressive Video Generation (2605.26105).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26105", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.26102", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "InstructSAM: Segment Any Instance with Any Instructions", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for InstructSAM: Segment Any Instance with Any Instructions (2605.26102).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26102", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23986", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing (2605.23986).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23986", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.25971", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents (2605.25971).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25971", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26089", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Channel-wise Vector Quantization", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Channel-wise Vector Quantization (2605.26089).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26089", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.21748", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RankJudge: A Multi-Turn LLM-as-a-Judge Synthetic Benchmark Generator", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RankJudge: A Multi-Turn LLM-as-a-Judge Synthetic Benchmark Generator (2605.21748).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21748", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26109", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Helix4D: Complex 4D Mesh Generation", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Helix4D: Complex 4D Mesh Generation (2605.26109).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26109", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25052", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Faithfulness Metrics Don't Measure Faithfulness: A Meta-Evaluation with Ground Truth", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Faithfulness Metrics Don't Measure Faithfulness: A Meta-Evaluation with Ground Truth (2605.25052).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25052", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.24213", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild (2605.24213).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24213", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26099", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Language Models Need Sleep", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Language Models Need Sleep (2605.26099).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26099", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25294", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometry-Aware Image Flow Matching", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geometry-Aware Image Flow Matching (2605.25294).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25294", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.24426", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SEAL: Synergistic Co-Evolution of Agents and Learning Environments", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SEAL: Synergistic Co-Evolution of Agents and Learning Environments (2605.24426).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24426", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23699", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models (2605.23699).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23699", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08129", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Customized Multimodal Role-Play", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Towards Customized Multimodal Role-Play (2605.08129).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08129", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.23491", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test (2605.23491).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23491", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25461", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MetaphorVU: Towards Metaphorical Video Understanding", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MetaphorVU: Towards Metaphorical Video Understanding (2605.25461).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25461", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.25160", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SimuWoB: Simulating Real-World Mobile Apps for Fast and Faithful GUI Agent Benchmarking", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SimuWoB: Simulating Real-World Mobile Apps for Fast and Faithful GUI Agent Benchmarking (2605.25160).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25160", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.26502", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design (2605.26502).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26502", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24517", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ECHO: Terminal Agents Learn World Models for Free", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ECHO: Terminal Agents Learn World Models for Free (2605.24517).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24517", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23264", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution (2605.23264).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23264", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.22880", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "How Far Will They Go? Red-Teaming Online Influence with Large Language Models", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for How Far Will They Go? Red-Teaming Online Influence with Large Language Models (2605.22880).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22880", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26108", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reinforcing Few-step Generators via Reward-Tilted Distribution Matching", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Reinforcing Few-step Generators via Reward-Tilted Distribution Matching (2605.26108).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.26108", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25191", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Injecting Image Guidance into Text-Conditioned Diffusion Models at Inference", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Injecting Image Guidance into Text-Conditioned Diffusion Models at Inference (2605.25191).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.25191", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2604.13517", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Representation over Routing: Diagnosing Temporal Routing Pathologies in Multi-Timescale PPO", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Representation over Routing: Diagnosing Temporal Routing Pathologies in Multi-Timescale PPO (2604.13517).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.13517", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.26449", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Cross-scale Aligned Supervision for Training GANs", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Cross-scale Aligned Supervision for Training GANs (2605.26449).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26449", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.26095", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Pixel-Level Pavement Distress Assessment Using Instance Segmentation", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Pixel-Level Pavement Distress Assessment Using Instance Segmentation (2605.26095).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26095", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.26002", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SemBridge: Language Transfer in Sparse Encoders via Multilingual Semantic Bridges", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SemBridge: Language Transfer in Sparse Encoders via Multilingual Semantic Bridges (2605.26002).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.26002", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.25189", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models (2605.25189).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.25189", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23889", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HorizonStream: Long-Horizon Attention for Streaming 3D Reconstruction", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for HorizonStream: Long-Horizon Attention for Streaming 3D Reconstruction (2605.23889).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.23889", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22818", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MotiMotion: Motion-Controlled Video Generation with Visual Reasoning", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for MotiMotion: Motion-Controlled Video Generation with Visual Reasoning (2605.22818).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22818", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.21712", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries (2605.21712).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21712", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21085", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Decoupling Communication from Policy: Robust MARL under Bandwidth Constraints", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Decoupling Communication from Policy: Robust MARL under Bandwidth Constraints (2605.21085).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21085", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20278", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison (2605.20278).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20278", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10988", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation (2605.10988).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.10988", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2603.16331", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Decoding the Critique Mechanism in Large Reasoning Models", "date": "2026-05-26", "createdAt": "2026-05-26", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Decoding the Critique Mechanism in Large Reasoning Models (2603.16331).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2603.16331", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:just-me7ss/American-Sign-Language-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "just-me7ss/American-Sign-Language-Dataset", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 273318 downloads.", "popularity": {"value": 273318, "label": "downloads"}, "url": "https://huggingface.co/datasets/just-me7ss/American-Sign-Language-Dataset", "tags": ["american sign language", "asl", "datasets", "gesture recognition", "license:mit", "modality:video", "region:us", "video dataset"]}
{"id": "paper:arxiv:2605.23904", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillOpt: Executive Strategy for Self-Evolving Agent Skills", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "SkillOpt introduces a systematic text-space optimizer for agent skills that trains skills as external agent state with stable updates and zero deployment inference overhead, achieving superior performance across multiple benchmarks and execution environment...", "popularity": {"value": 216, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23904", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20708", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking Cross-Layer Information Routing in Diffusion Transformers", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking Cross-Layer Information Routing in Diffusion Transformers (2605.20708).", "popularity": {"value": 109, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20708", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.21573", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models (2605.21573).", "popularity": {"value": 107, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21573", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.22878", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research (2605.22878).", "popularity": {"value": 58, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22878", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.23463", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StepAudio 2.5 Technical Report", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StepAudio 2.5 Technical Report (2605.23463).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23463", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23902", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion (2605.23902).", "popularity": {"value": 45, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23902", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.18018", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding (2605.18018).", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18018", "tags": ["huggingface-papers", "paper", "research", "video-generation", "vision"]}
{"id": "paper:arxiv:2605.23899", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills (2605.23899).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23899", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23771", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhotoFlow: Agentic 3D Virtual Photography Missions", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhotoFlow: Agentic 3D Virtual Photography Missions (2605.23771).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23771", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22570", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis (2605.22570).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22570", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21195", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution (2605.21195).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21195", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.17448", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback (2605.17448).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17448", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23345", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models (2605.23345).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23345", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23901", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws (2605.23901).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23901", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23897", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ETCHR: Editing To Clarify and Harness Reasoning", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ETCHR: Editing To Clarify and Harness Reasoning (2605.23897).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23897", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.23888", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction (2605.23888).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23888", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17873", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HINT-SD: Targeted Hindsight Self-Distillation for Long-Horizon Agents", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HINT-SD: Targeted Hindsight Self-Distillation for Long-Horizon Agents (2605.17873).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17873", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.23903", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geo-Align: Video Generation Alignment via Metric Geometry Reward", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geo-Align: Video Generation Alignment via Metric Geometry Reward (2605.23903).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23903", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.20177", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models (2605.20177).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20177", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.23892", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Good Token Hunting: A Hitchhiker's Guide to Token Selection for Visual Geometry Transformers", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Good Token Hunting: A Hitchhiker's Guide to Token Selection for Visual Geometry Transformers (2605.23892).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.23892", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21856", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation (2605.21856).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21856", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19282", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR (2605.19282).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19282", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17766", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LatentUMM: Dual Latent Alignment for Unified Multimodal Models", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LatentUMM: Dual Latent Alignment for Unified Multimodal Models (2605.17766).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17766", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2604.20665", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Expense of Seeing: Attaining Trustworthy Multimodal Reasoning Within the Monolithic Paradigm", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Expense of Seeing: Attaining Trustworthy Multimodal Reasoning Within the Monolithic Paradigm (2604.20665).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.20665", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.21488", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning (2605.21488).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21488", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24681", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs (2605.24681).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.24681", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.24675", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VaaWIT: Visual-Aware Adaptation of Large Language Models for Multilingual Web Image Translation", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for VaaWIT: Visual-Aware Adaptation of Large Language Models for Multilingual Web Image Translation (2605.24675).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.24675", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.19354", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Next-Acceleration-Scale Prediction for Autoregressive MRI Reconstruction", "date": "2026-05-25", "createdAt": "2026-05-25", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Next-Acceleration-Scale Prediction for Autoregressive MRI Reconstruction (2605.19354).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19354", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21467", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Reinforcement learning from verifiable rewards is enhanced through a discriminative token credit assignment method that improves reward-based training by amplifying distinctive token-gradient directions and reducing noise from shared patterns. Reinforcement...", "popularity": {"value": 204, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21467", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.22355", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "TransitLM dataset enables end-to-end transit route planning using large language models trained on structured transit data, eliminating the need for traditional map-based approaches. Public transit route planning traditionally depends on structured map infr...", "popularity": {"value": 174, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22355", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22109", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Researchers introduce a new task and dataset for evaluating personality reasoning in multimodal language models, revealing significant gaps between accurate predictions and grounded reasoning processes. Multimodal Large Language Models (MLLMs) are increasin...", "popularity": {"value": 169, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22109", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14678", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "π-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for π-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows (2605.14678).", "popularity": {"value": 102, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14678", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.16928", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps (2605.16928).", "popularity": {"value": 93, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16928", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21850", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ACC: Compiling Agent Trajectories for Long-Context Training", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ACC: Compiling Agent Trajectories for Long-Context Training (2605.21850).", "popularity": {"value": 58, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21850", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21572", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects (2605.21572).", "popularity": {"value": 52, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21572", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22012", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning (2605.22012).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22012", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.22681", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Forecasting Scientific Progress with Artificial Intelligence", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Forecasting Scientific Progress with Artificial Intelligence (2605.22681).", "popularity": {"value": 43, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22681", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22718", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WorldKV: Efficient World Memory with World Retrieval and Compression", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WorldKV: Efficient World Memory with World Retrieval and Compression (2605.22718).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22718", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.22668", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers (2605.22668).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22668", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.22642", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning (2605.22642).", "popularity": {"value": 35, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22642", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22791", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention (2605.22791).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22791", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20910", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FlowLong: Inference-time Long Video Generation via Manifold-constrained Tweedie Matching", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FlowLong: Inference-time Long Video Generation via Manifold-constrained Tweedie Matching (2605.20910).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20910", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.22536", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation (2605.22536).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22536", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22809", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Sensor2Sensor: Cross-Embodiment Sensor Conversion for Autonomous Driving", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Sensor2Sensor: Cross-Embodiment Sensor Conversion for Autonomous Driving (2605.22809).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22809", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10158", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Unsupervised Process Reward Models", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Unsupervised Process Reward Models (2605.10158).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10158", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21072", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Q-ARVD: Quantizing Autoregressive Video Diffusion Models", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Q-ARVD: Quantizing Autoregressive Video Diffusion Models (2605.21072).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21072", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.22177", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles (2605.22177).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22177", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17602", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment (2605.17602).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17602", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.12817", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Training Large Language Models to Predict Clinical Events", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Training Large Language Models to Predict Clinical Events (2605.12817).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12817", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22344", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Bernini: Latent Semantic Planning for Video Diffusion", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Bernini: Latent Semantic Planning for Video Diffusion (2605.22344).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22344", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18607", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Forecasting Downstream Performance of LLMs With Proxy Metrics", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Forecasting Downstream Performance of LLMs With Proxy Metrics (2605.18607).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18607", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21605", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation (2605.21605).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21605", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20176", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning (2605.20176).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20176", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13734", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving (2605.13734).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13734", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.22678", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Swift Sampling: Selecting Temporal Surprises via Taylor Series", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Swift Sampling: Selecting Temporal Surprises via Taylor Series (2605.22678).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22678", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22138", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Efficient Agentic Reasoning Through Self-Regulated Simulative Planning", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Efficient Agentic Reasoning Through Self-Regulated Simulative Planning (2605.22138).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22138", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22144", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems (2605.22144).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22144", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22535", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks (2605.22535).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22535", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13163", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LoREnc: Low-Rank Encryption for Securing Foundation Models and LoRA Adapters", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LoREnc: Low-Rank Encryption for Securing Foundation Models and LoRA Adapters (2605.13163).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13163", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22581", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SceneAligner: 3D-Grounded Floorplan Localization in the Wild", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SceneAligner: 3D-Grounded Floorplan Localization in the Wild (2605.22581).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22581", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.15669", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation (2605.15669).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15669", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22766", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Diversed Model Discovery via Structured Table Discovery", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Diversed Model Discovery via Structured Table Discovery (2605.22766).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22766", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22538", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking (2605.22538).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22538", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21363", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "\"I didn't Make the Micro Decisions\": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for \"I didn't Make the Micro Decisions\": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration (2605.21363).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21363", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22777", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders (2605.22777).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.22777", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18577", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniPro: A Comprehensive Benchmark for Omni-Proactive Streaming Video Understanding", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OmniPro: A Comprehensive Benchmark for Omni-Proactive Streaming Video Understanding (2605.18577).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18577", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22717", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators (2605.22717).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22717", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.22715", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild (2605.22715).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22715", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.22641", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts (2605.22641).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22641", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.22552", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning (2605.22552).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.22552", "tags": ["huggingface-papers", "paper", "rag", "research"]}
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{"id": "paper:arxiv:2605.20496", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Platonic Representations in the Human Brain: Unsupervised Recovery of Universal Geometry", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Platonic Representations in the Human Brain: Unsupervised Recovery of Universal Geometry (2605.20496).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20496", "tags": ["huggingface-papers", "llm", "paper", "research"]}
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{"id": "paper:arxiv:2605.20244", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search (2605.20244).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20244", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19990", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Minimalist Visual Inertial Odometry", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Minimalist Visual Inertial Odometry (2605.19990).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19990", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07604", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SAM 3D Animal: Promptable Animal 3D Reconstruction from Images in the Wild", "date": "2026-05-24", "createdAt": "2026-05-24", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SAM 3D Animal: Promptable Animal 3D Reconstruction from Images in the Wild (2605.07604).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.07604", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "hf-dataset:idacy/control-arena-persistent-state-eval-logs-2026-05-23", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "idacy/control-arena-persistent-state-eval-logs-2026-05-23", "date": "2026-05-23", "createdAt": "2026-05-23", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47554 downloads.", "popularity": {"value": 47554, "label": "downloads"}, "url": "https://huggingface.co/datasets/idacy/control-arena-persistent-state-eval-logs-2026-05-23", "tags": ["datasets", "region:us"]}
{"id": "paper:arxiv:2605.14747", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining (2605.14747).", "popularity": {"value": 145, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14747", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20613", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HRM-Text: Efficient Pretraining Beyond Scaling", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HRM-Text: Efficient Pretraining Beyond Scaling (2605.20613).", "popularity": {"value": 131, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20613", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.19833", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation (2605.19833).", "popularity": {"value": 131, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19833", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18233", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos (2605.18233).", "popularity": {"value": 92, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18233", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.20682", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools (2605.20682).", "popularity": {"value": 83, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20682", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20266", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook (2605.20266).", "popularity": {"value": 56, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20266", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21468", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories (2605.21468).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21468", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20873", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models (2605.20873).", "popularity": {"value": 43, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20873", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19660", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond (2605.19660).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19660", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.20119", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Toto 2.0: Time Series Forecasting Enters the Scaling Era", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Toto 2.0: Time Series Forecasting Enters the Scaling Era (2605.20119).", "popularity": {"value": 38, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20119", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20258", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs (2605.20258).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20258", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19376", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Generative Recursive Reasoning", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Generative Recursive Reasoning (2605.19376).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19376", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20315", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs (2605.20315).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20315", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21487", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning (2605.21487).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21487", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19484", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CutVerse: A Compositional GUI Agents Benchmark for Media Post-Production Editing", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CutVerse: A Compositional GUI Agents Benchmark for Media Post-Production Editing (2605.19484).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19484", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19597", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening (2605.19597).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19597", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17991", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stable Audio 3", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stable Audio 3 (2605.17991).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17991", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20668", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists (2605.20668).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20668", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20630", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines (2605.20630).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20630", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19804", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stitched Value Model for Diffusion Alignment", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stitched Value Model for Diffusion Alignment (2605.19804).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19804", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2604.27263", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation (2604.27263).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.27263", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21981", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RiT: Vanilla Diffusion Transformers Suffice in Representation Space", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RiT: Vanilla Diffusion Transformers Suffice in Representation Space (2605.21981).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21981", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.15113", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning from Language Feedback via Variational Policy Distillation", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning from Language Feedback via Variational Policy Distillation (2605.15113).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15113", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.21226", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OCTOPUS: Optimized KV Cache for Transformers via Octahedral Parametrization Under optimal Squared error quantization", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OCTOPUS: Optimized KV Cache for Transformers via Octahedral Parametrization Under optimal Squared error quantization (2605.21226).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21226", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.21343", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation (2605.21343).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21343", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.21131", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniT: Unified Geometry Learning with Group Autoregressive Transformer", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UniT: Unified Geometry Learning with Group Autoregressive Transformer (2605.21131).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21131", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19330", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization (2605.19330).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19330", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17526", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering (2605.17526).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17526", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21463", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mem-π: Adaptive Memory through Learning When and What to Generate", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mem-π: Adaptive Memory through Learning When and What to Generate (2605.21463).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.21463", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16787", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Unlearnability Phenomenon in RLVR for Language Models", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Unlearnability Phenomenon in RLVR for Language Models (2605.16787).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16787", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20834", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Conditional Equivalence of DPO and RLHF: Implicit Assumption, Failure Modes, and Provable Alignment", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Conditional Equivalence of DPO and RLHF: Implicit Assumption, Failure Modes, and Provable Alignment (2605.20834).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20834", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18565", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MINTEval: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MINTEval: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems (2605.18565).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18565", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.21431", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance (2605.21431).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21431", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.21384", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents (2605.21384).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.21384", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20955", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DrawMotion: Generating 3D Human Motions by Freehand Drawing", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for DrawMotion: Generating 3D Human Motions by Freehand Drawing (2605.20955).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20955", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20179", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for TIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload (2605.20179).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20179", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.20158", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models (2605.20158).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20158", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.19008", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learn-by-Wire Training Control Governance: Bounded Autonomous Training Under Stress for Stability and Efficiency", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Learn-by-Wire Training Control Governance: Bounded Autonomous Training Under Stress for Stability and Efficiency (2605.19008).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19008", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18329", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation (2605.18329).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18329", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17916", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PanoWorld: A Generative Spatial World Model for Consistent Whole-House Panorama Synthesis", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for PanoWorld: A Generative Spatial World Model for Consistent Whole-House Panorama Synthesis (2605.17916).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17916", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17110", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Capturing LLM Capabilities via Evidence-Calibrated Query Clustering", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Capturing LLM Capabilities via Evidence-Calibrated Query Clustering (2605.17110).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17110", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17109", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DynMuon: A Dynamic Spectral Shaping View of Muon", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for DynMuon: A Dynamic Spectral Shaping View of Muon (2605.17109).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17109", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2602.07892", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection", "date": "2026-05-21", "createdAt": "2026-05-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection (2602.07892).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2602.07892", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.11609", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Anti-Self-Distillation for Reasoning RL via Pointwise Mutual Information", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Anti-Self-Distillation reverses the direction of knowledge transfer in self-distillation to improve math reasoning efficiency and accuracy. On-policy self-distillation , where a student is pulled toward a copy of itself conditioned on privileged context (e....", "popularity": {"value": 195, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11609", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20025", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "AutoResearchClaw is a multi-agent autonomous research system that improves scientific discovery through structured debate, self-healing execution, verifiable reporting, human collaboration, and evolutionary learning, outperforming previous systems on a benc...", "popularity": {"value": 185, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20025", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.16403", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When Vision Speaks for Sound", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When Vision Speaks for Sound (2605.16403).", "popularity": {"value": 149, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16403", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.14236", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Active Learners as Efficient PRP Rerankers", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Active Learners as Efficient PRP Rerankers (2605.14236).", "popularity": {"value": 98, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14236", "tags": ["embeddings", "huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.19769", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OpenComputer: Verifiable Software Worlds for Computer-Use Agents", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OpenComputer: Verifiable Software Worlds for Computer-Use Agents (2605.19769).", "popularity": {"value": 81, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19769", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19577", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment (2605.19577).", "popularity": {"value": 58, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19577", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15529", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Process Rewards with Learned Reliability", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Process Rewards with Learned Reliability (2605.15529).", "popularity": {"value": 53, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15529", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18703", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL (2605.18703).", "popularity": {"value": 50, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18703", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17734", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Harnessing LLM Agents with Skill Programs", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Harnessing LLM Agents with Skill Programs (2605.17734).", "popularity": {"value": 36, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17734", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19995", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition (2605.19995).", "popularity": {"value": 34, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19995", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.18748", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Aurora: Unified Video Editing with a Tool-Using Agent", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Aurora: Unified Video Editing with a Tool-Using Agent (2605.18748).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18748", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18984", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos (2605.18984).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18984", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20087", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions (2605.20087).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20087", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18758", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments (2605.18758).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18758", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20183", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation (2605.20183).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20183", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19436", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization (2605.19436).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19436", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17829", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Interactive Evaluation Requires a Design Science", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Interactive Evaluation Requires a Design Science (2605.17829).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17829", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18101", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SENSE: Satellite-based ENergy Synthesis for Sustainable Environment", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SENSE: Satellite-based ENergy Synthesis for Sustainable Environment (2605.18101).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18101", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20147", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset (2605.20147).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20147", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.18714", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Semantic Generative Tuning for Unified Multimodal Models", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Semantic Generative Tuning for Unified Multimodal Models (2605.18714).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18714", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.15458", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Video Models Can Reason with Verifiable Rewards", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Video Models Can Reason with Verifiable Rewards (2605.15458).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15458", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.19786", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Fast 4D Mesh Generation by Spatio-Temporal Attention Chains", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Fast 4D Mesh Generation by Spatio-Temporal Attention Chains (2605.19786).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19786", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18263", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RT-Splatting: Joint Reflection-Transmission Modeling with Gaussian Splatting", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RT-Splatting: Joint Reflection-Transmission Modeling with Gaussian Splatting (2605.18263).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18263", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18855", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Delta Attention Residuals", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Delta Attention Residuals (2605.18855).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18855", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09640", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning (2605.09640).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09640", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20150", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization (2605.20150).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20150", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20104", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding (2605.20104).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20104", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.19932", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PEEK: Context Map as an Orientation Cache for Long-Context LLM Agents", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PEEK: Context Map as an Orientation Cache for Long-Context LLM Agents (2605.19932).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19932", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18827", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds (2605.18827).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18827", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.20164", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR (2605.20164).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20164", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19633", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "optimize_anything: A Universal API for Optimizing any Text Parameter", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for optimize_anything: A Universal API for Optimizing any Text Parameter (2605.19633).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19633", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19305", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Matérn Noise for Triangulation-Agnostic Flow Matching on Meshes", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Matérn Noise for Triangulation-Agnostic Flow Matching on Meshes (2605.19305).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19305", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18226", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Context Memorization for Efficient Long Context Generation", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Context Memorization for Efficient Long Context Generation (2605.18226).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18226", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.09789", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching (2605.09789).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09789", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20035", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stage-adaptive Token Selection for Efficient Omni-modal LLMs", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stage-adaptive Token Selection for Efficient Omni-modal LLMs (2605.20035).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.20035", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.19908", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Where Does Authorship Signal Emerge in Encoder-Based Language Models?", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Where Does Authorship Signal Emerge in Encoder-Based Language Models? (2605.19908).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.19908", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18746", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop (2605.18746).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18746", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16003", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation (2605.16003).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16003", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.08472", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mid-Training with Self-Generated Data Improves Reinforcement Learning in Language Models", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mid-Training with Self-Generated Data Improves Reinforcement Learning in Language Models (2605.08472).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08472", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.20075", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning (2605.20075).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.20075", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19516", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Base Models Look Human To AI Detectors", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Base Models Look Human To AI Detectors (2605.19516).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19516", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.19147", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks (2605.19147).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19147", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.19014", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction (2605.19014).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.19014", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18646", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Language-Switching Triggers Take a Latent Detour Through Language Models", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Language-Switching Triggers Take a Latent Detour Through Language Models (2605.18646).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18646", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17909", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Ethical Hyper-Velocity (EHV): A Provably Deterministic Governance-Aware JIT Compiler Architecture for Agentic Systems", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Ethical Hyper-Velocity (EHV): A Provably Deterministic Governance-Aware JIT Compiler Architecture for Agentic Systems (2605.17909).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17909", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17659", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Bug or Feature^2: Weight Drift, Activation Sparsity, and Spikes", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Bug or Feature^2: Weight Drift, Activation Sparsity, and Spikes (2605.17659).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17659", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17360", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction (2605.17360).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17360", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17076", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "S-Bus: Automatic Read-Set Reconstruction for Multi-Agent LLM State Coordination", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for S-Bus: Automatic Read-Set Reconstruction for Multi-Agent LLM State Coordination (2605.17076).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17076", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17026", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road (2605.17026).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17026", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.15514", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably (2605.15514).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15514", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14842", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Editor's Choice: Evaluating Abstract Intent in Image Editing through Atomic Entity Analysis", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Editor's Choice: Evaluating Abstract Intent in Image Editing through Atomic Entity Analysis (2605.14842).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14842", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12623", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DocAtlas: Multilingual Document Understanding Across 80+ Languages", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for DocAtlas: Multilingual Document Understanding Across 80+ Languages (2605.12623).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12623", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08586", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Computer Science Conferences Should Require Nonrepudiable Experimental Results", "date": "2026-05-20", "createdAt": "2026-05-20", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Computer Science Conferences Should Require Nonrepudiable Experimental Results (2605.08586).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08586", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:1111xxx/zoengjyutgaai", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "1111xxx/zoengjyutgaai", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55950 downloads.", "popularity": {"value": 55950, "label": "downloads"}, "url": "https://huggingface.co/datasets/1111xxx/zoengjyutgaai", "tags": ["art", "audio", "cantonese", "datasets", "language:yue", "license:cc0-1.0", "modality:audio", "region:us"]}
{"id": "hf-dataset:Wan-fen52/MAVOS-DD", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Wan-fen52/MAVOS-DD", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52911 downloads.", "popularity": {"value": 52911, "label": "downloads"}, "url": "https://huggingface.co/datasets/Wan-fen52/MAVOS-DD", "tags": ["arxiv:2505.11109", "datasets", "language:ar", "language:de", "language:en", "language:es", "language:hi", "language:ro"]}
{"id": "paper:arxiv:2605.18747", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Code as Agent Harness", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Large language models are increasingly used as operational substrates for agent reasoning and execution in agentic systems, with code serving as a unified infrastructure layer across multiple domains and applications. Recent large language models (LLMs) hav...", "popularity": {"value": 211, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18747", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18401", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution (2605.18401).", "popularity": {"value": 126, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18401", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18739", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation (2605.18739).", "popularity": {"value": 112, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18739", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.18678", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lance: Unified Multimodal Modeling by Multi-Task Synergy", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Lance: Unified Multimodal Modeling by Multi-Task Synergy (2605.18678).", "popularity": {"value": 78, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18678", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.18661", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AI for Auto-Research: Roadmap & User Guide", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AI for Auto-Research: Roadmap & User Guide (2605.18661).", "popularity": {"value": 67, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18661", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17757", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization (2605.17757).", "popularity": {"value": 63, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17757", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.16679", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows? (2605.16679).", "popularity": {"value": 53, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16679", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18451", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis (2605.18451).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18451", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14278", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration (2605.14278).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14278", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17283", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OProver: A Unified Framework for Agentic Formal Theorem Proving", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OProver: A Unified Framework for Agentic Formal Theorem Proving (2605.17283).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17283", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18643", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Post-Trained MoE Can Skip Half Experts via Self-Distillation", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Post-Trained MoE Can Skip Half Experts via Self-Distillation (2605.18643).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18643", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16079", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation (2605.16079).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16079", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17260", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs (2605.17260).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17260", "tags": ["huggingface-papers", "paper", "research", "small-local", "video-generation"]}
{"id": "paper:arxiv:2605.17672", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models (2605.17672).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17672", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.15572", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Measuring Maximum Activations in Open Large Language Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Measuring Maximum Activations in Open Large Language Models (2605.15572).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15572", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14589", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EndPrompt: Efficient Long-Context Extension via Terminal Anchoring", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EndPrompt: Efficient Long-Context Extension via Terminal Anchoring (2605.14589).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14589", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.15565", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs (2605.15565).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15565", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18287", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StableVLA: Towards Robust Vision-Language-Action Models without Extra Data", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StableVLA: Towards Robust Vision-Language-Action Models without Extra Data (2605.18287).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18287", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.14038", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use (2605.14038).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14038", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12290", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Targeted Neuron Modulation via Contrastive Pair Search", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Targeted Neuron Modulation via Contrastive Pair Search (2605.12290).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12290", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14368", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement (2605.14368).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14368", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.16839", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection (2605.16839).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16839", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17242", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Runnable to Shippable: Multi-Agent Test-Driven Development for Generating Full-Stack Web Applications from Requirements", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Runnable to Shippable: Multi-Agent Test-Driven Development for Generating Full-Stack Web Applications from Requirements (2605.17242).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17242", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18749", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WavFlow: Audio Generation in Waveform Space", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WavFlow: Audio Generation in Waveform Space (2605.18749).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18749", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16893", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NGM: A Plug-and-Play Training-Free Memory Module for LLMs", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for NGM: A Plug-and-Play Training-Free Memory Module for LLMs (2605.16893).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16893", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16909", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents (2605.16909).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16909", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18652", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents (2605.18652).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18652", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15482", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FINESSE-Bench: A Hierarchical Benchmark Suite for Financial Domain Knowledge and Technical Analysis in Large Language Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FINESSE-Bench: A Hierarchical Benchmark Suite for Financial Domain Knowledge and Technical Analysis in Large Language Models (2605.15482).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15482", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18727", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DexHoldem: Playing Texas Hold'em with Dexterous Embodied System", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DexHoldem: Playing Texas Hold'em with Dexterous Embodied System (2605.18727).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18727", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.17933", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AtlasVA: Self-Evolving Visual Skill Memory for Teacher-Free VLM Agents", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AtlasVA: Self-Evolving Visual Skill Memory for Teacher-Free VLM Agents (2605.17933).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17933", "tags": ["agents", "huggingface-papers", "paper", "research"]}
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{"id": "paper:arxiv:2605.18601", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models (2605.18601).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18601", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.17698", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplaces", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplaces (2605.17698).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17698", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17199", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity (2605.17199).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17199", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18719", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training (2605.18719).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.18719", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.17894", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Evaluating Cognitive Age Alignment in Interactive AI Agents", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Evaluating Cognitive Age Alignment in Interactive AI Agents (2605.17894).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.17894", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18743", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Actionable World Representation", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Actionable World Representation (2605.18743).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18743", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18630", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science (2605.18630).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18630", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.18549", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics (2605.18549).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18549", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.18106", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers (2605.18106).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.18106", "tags": ["embeddings", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.17842", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SNLP: Layer-Parallel Inference via Structured Newton Corrections", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SNLP: Layer-Parallel Inference via Structured Newton Corrections (2605.17842).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17842", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.17278", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation (2605.17278).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.17278", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.16882", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "E-PMQ: Expert-Guided Post-Merge Quantization with Merged-Weight Anchoring", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for E-PMQ: Expert-Guided Post-Merge Quantization with Merged-Weight Anchoring (2605.16882).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.16882", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.16819", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents (2605.16819).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.16819", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.16386", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring (2605.16386).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.16386", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.15764", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions (2605.15764).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15764", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15035", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TopoPrimer: The Missing Topological Context in Forecasting Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for TopoPrimer: The Missing Topological Context in Forecasting Models (2605.15035).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15035", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2603.10126", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AR-VLA: True Autoregressive Action Expert for Vision-Language-Action Models", "date": "2026-05-19", "createdAt": "2026-05-19", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AR-VLA: True Autoregressive Action Expert for Vision-Language-Action Models (2603.10126).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2603.10126", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "github:lynote-ai/humanize-text", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lynote-ai/humanize-text", "date": "2026-06-01", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Free open-source AI text humanizer to convert AI-generated content into undetectable, human-like writing. Bypass Turnitin, GPTZero, and all major AI detectors. No sign-up required. Try our unlimited free online tool", "popularity": {"value": 1069, "label": "stars"}, "url": "https://github.com/lynote-ai/humanize-text", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:hrz2001/Maritime_Visual_Tracking_Dataset_MVTD", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hrz2001/Maritime_Visual_Tracking_Dataset_MVTD", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53447 downloads.", "popularity": {"value": 53447, "label": "downloads"}, "url": "https://huggingface.co/datasets/hrz2001/Maritime_Visual_Tracking_Dataset_MVTD", "tags": ["arxiv:2506.02866", "datasets", "license:cc0-1.0", "region:us", "size_categories:100k<n<1m"]}
{"id": "paper:arxiv:2605.12882", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CiteVQA: Benchmarking Evidence Attribution for Trustworthy Document Intelligence", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "CiteVQA introduces a benchmark for document vision-language models that evaluates both answer accuracy and correct citation of supporting evidence, revealing significant attribution hallucinations in current models. Multimodal Large Language Models (MLLMs)...", "popularity": {"value": 270, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12882", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.15298", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhysBrain 1.0 Technical Report", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhysBrain 1.0 Technical Report (2605.15298).", "popularity": {"value": 143, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15298", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13527", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MMSkills: Towards Multimodal Skills for General Visual Agents", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MMSkills: Towards Multimodal Skills for General Visual Agents (2605.13527).", "popularity": {"value": 118, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13527", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15824", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization (2605.15824).", "popularity": {"value": 64, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15824", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.11739", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation (2605.11739).", "popularity": {"value": 59, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11739", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14271", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Auditing Agent Harness Safety", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Auditing Agent Harness Safety (2605.14271).", "popularity": {"value": 54, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14271", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.16257", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo (2605.16257).", "popularity": {"value": 53, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16257", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02290", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding (2605.02290).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02290", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15980", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization (2605.15980).", "popularity": {"value": 36, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15980", "tags": ["huggingface-papers", "image-generation", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.14333", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation (2605.14333).", "popularity": {"value": 35, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14333", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
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{"id": "paper:arxiv:2605.15256", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ReactiveGWM: Steering NPC in Reactive Game World Models", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ReactiveGWM: Steering NPC in Reactive Game World Models (2605.15256).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15256", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15301", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution (2605.15301).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15301", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12058", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Hölder Policy Optimisation", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Hölder Policy Optimisation (2605.12058).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12058", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14212", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning (2605.14212).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14212", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15963", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control (2605.15963).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15963", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15871", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agentic Discovery of Neural Architectures: AIRA-Compose and AIRA-Design", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agentic Discovery of Neural Architectures: AIRA-Compose and AIRA-Design (2605.15871).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15871", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15876", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Unlocking Dense Metric Depth Estimation in VLMs", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Unlocking Dense Metric Depth Estimation in VLMs (2605.15876).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15876", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.15250", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GQLA: Group-Query Latent Attention for Hardware-Adaptive Large Language Model Decoding", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for GQLA: Group-Query Latent Attention for Hardware-Adaptive Large Language Model Decoding (2605.15250).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15250", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15181", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing (2605.15181).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15181", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2604.09839", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Steered LLM Activations are Non-Surjective", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Steered LLM Activations are Non-Surjective (2604.09839).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.09839", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15597", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage (2605.15597).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15597", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.05945", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware (2605.05945).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05945", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.16143", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Look Before You Leap: Autonomous Exploration for LLM Agents", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Look Before You Leap: Autonomous Exploration for LLM Agents (2605.16143).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.16143", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15961", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models (2605.15961).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15961", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15592", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Efficient Image Synthesis with Sphere Latent Encoder", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Efficient Image Synthesis with Sphere Latent Encoder (2605.15592).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15592", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.15320", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction (2605.15320).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15320", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08614", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules (2605.08614).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08614", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15843", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WorldAct: Activating Monolithic 3D Worlds into Interactive-Ready Object-Centric Scenes", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WorldAct: Activating Monolithic 3D Worlds into Interactive-Ready Object-Centric Scenes (2605.15843).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15843", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15138", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Forgetting That Sticks: Quantization-Permanent Unlearning via Circuit Attribution", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Forgetting That Sticks: Quantization-Permanent Unlearning via Circuit Attribution (2605.15138).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15138", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.13740", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning POMDP World Models from Observations with Language-Model Priors", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning POMDP World Models from Observations with Language-Model Priors (2605.13740).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13740", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15375", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing (2605.15375).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15375", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14539", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning from Failures: Correction-Oriented Policy Optimization with Verifiable Rewards", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning from Failures: Correction-Oriented Policy Optimization with Verifiable Rewards (2605.14539).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14539", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14040", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning (2605.14040).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14040", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13997", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts (2605.13997).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13997", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.10302", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Follow the Mean: Reference-Guided Flow Matching", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Follow the Mean: Reference-Guided Flow Matching (2605.10302).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10302", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2602.09016", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Raster2Seq: Polygon Sequence Generation for Floorplan Reconstruction", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Raster2Seq: Polygon Sequence Generation for Floorplan Reconstruction (2602.09016).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2602.09016", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14786", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces (2605.14786).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14786", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12678", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "No One Knows the State of the Art in Geospatial Foundation Models", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for No One Knows the State of the Art in Geospatial Foundation Models (2605.12678).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12678", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12524", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stress-Testing the Reasoning Competence of LLMs With Proofs Under Minimal Formalism", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Stress-Testing the Reasoning Competence of LLMs With Proofs Under Minimal Formalism (2605.12524).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12524", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12038", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation (2605.12038).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12038", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.07249", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MLAIRE: Multilingual Language-Aware Information Retrieval Evaluation Protocal", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for MLAIRE: Multilingual Language-Aware Information Retrieval Evaluation Protocal (2605.07249).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.07249", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2506.01015", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AuralSAM2: Enabling SAM2 Hear Through Pyramid Audio-Visual Feature Prompting", "date": "2026-05-18", "createdAt": "2026-05-18", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AuralSAM2: Enabling SAM2 Hear Through Pyramid Audio-Visual Feature Prompting (2506.01015).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2506.01015", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.13301", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "A systematic approach transforms post-trained reasoning models into rigorous olympiad-level solvers through reverse-perplexity curriculum, two-stage reinforcement learning, and test-time scaling, achieving gold-medal performance on mathematical and physics...", "popularity": {"value": 159, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13301", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15155", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Self-Distilled Agentic Reinforcement Learning", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Self-Distilled Agentic Reinforcement Learning (2605.15155).", "popularity": {"value": 111, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15155", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15141", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation (2605.15141).", "popularity": {"value": 93, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15141", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.15178", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformer", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformer (2605.15178).", "popularity": {"value": 85, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15178", "tags": ["huggingface-papers", "image-generation", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.14906", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models (2605.14906).", "popularity": {"value": 76, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14906", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15128", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory (2605.15128).", "popularity": {"value": 62, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15128", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14386", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning (2605.14386).", "popularity": {"value": 60, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14386", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14892", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems (2605.14892).", "popularity": {"value": 48, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14892", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10912", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation (2605.10912).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10912", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06527", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for STALE: Can LLM Agents Know When Their Memories Are No Longer Valid? (2605.06527).", "popularity": {"value": 44, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06527", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15182", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video (2605.15182).", "popularity": {"value": 39, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15182", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.06554", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Long Context Pre-Training with Lighthouse Attention", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Long Context Pre-Training with Lighthouse Attention (2605.06554).", "popularity": {"value": 31, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06554", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.00180", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RouteProfile: Elucidating the Design Space of LLM Profiles for Routing", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RouteProfile: Elucidating the Design Space of LLM Profiles for Routing (2605.00180).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00180", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13880", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PREPING: Building Agent Memory without Tasks", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PREPING: Building Agent Memory without Tasks (2605.13880).", "popularity": {"value": 28, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13880", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15186", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction (2605.15186).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15186", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13852", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning (2605.13852).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13852", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13941", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents (2605.13941).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13941", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14445", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale (2605.14445).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14445", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13169", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PanoWorld: Towards Spatial Supersensing in 360^circ Panorama World", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PanoWorld: Towards Spatial Supersensing in 360^circ Panorama World (2605.13169).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13169", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15198", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both (2605.15198).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15198", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15055", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models (2605.15055).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15055", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.15040", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Orchard: An Open-Source Agentic Modeling Framework", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Orchard: An Open-Source Agentic Modeling Framework (2605.15040).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15040", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.07637", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding (2605.07637).", "popularity": {"value": 19, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07637", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14712", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "IntentVLA: Short-Horizon Intent Modeling for Aliased Robot Manipulation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for IntentVLA: Short-Horizon Intent Modeling for Aliased Robot Manipulation (2605.14712).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14712", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.15190", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RAVEN: Real-time Autoregressive Video Extrapolation with Consistency-model GRPO", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RAVEN: Real-time Autoregressive Video Extrapolation with Consistency-model GRPO (2605.15190).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15190", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.14607", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ViMU: Benchmarking Video Metaphorical Understanding", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ViMU: Benchmarking Video Metaphorical Understanding (2605.14607).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14607", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13027", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PRISM: Prior Rectification and Uncertainty-Aware Structure Modeling for Diffusion-Based Text Image Super-Resolution", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PRISM: Prior Rectification and Uncertainty-Aware Structure Modeling for Diffusion-Based Text Image Super-Resolution (2605.13027).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13027", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.09681", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Forcing-KV: Hybrid KV Cache Compression for Efficient Autoregressive Video Diffusion Models", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Forcing-KV: Hybrid KV Cache Compression for Efficient Autoregressive Video Diffusion Models (2605.09681).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09681", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.08703", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RewardHarness: Self-Evolving Agentic Post-Training", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RewardHarness: Self-Evolving Agentic Post-Training (2605.08703).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08703", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14269", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation (2605.14269).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14269", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.01018", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild (2605.01018).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01018", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15193", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Aligning Latent Geometry for Spherical Flow Matching in Image Generation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Aligning Latent Geometry for Spherical Flow Matching in Image Generation (2605.15193).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15193", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.15167", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Does Synthetic Layered Design Data Benefit Layered Design Decomposition?", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Does Synthetic Layered Design Data Benefit Layered Design Decomposition? (2605.15167).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15167", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14392", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis (2605.14392).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14392", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14169", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BOOKMARKS: Efficient Active Storyline Memory for Role-playing", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for BOOKMARKS: Efficient Active Storyline Memory for Role-playing (2605.14169).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14169", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.14068", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves (2605.14068).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14068", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15188", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FutureSim: Replaying World Events to Evaluate Adaptive Agents", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FutureSim: Replaying World Events to Evaluate Adaptive Agents (2605.15188).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.15188", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11458", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Adaptive Teacher Exposure for Self-Distillation in LLM Reasoning", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Adaptive Teacher Exposure for Self-Distillation in LLM Reasoning (2605.11458).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11458", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14389", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Nexus : An Agentic Framework for Time Series Forecasting", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Nexus : An Agentic Framework for Time Series Forecasting (2605.14389).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14389", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12034", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation (2605.12034).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12034", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14984", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image (2605.14984).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14984", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.14438", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE (2605.14438).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14438", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14354", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLM-based Detection of Manipulative Political Narratives", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLM-based Detection of Manipulative Political Narratives (2605.14354).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14354", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14352", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Ideology Prediction of German Political Texts", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Ideology Prediction of German Political Texts (2605.14352).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.14352", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13834", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Topology-Preserving Neural Operator Learning via Hodge Decomposition", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Topology-Preserving Neural Operator Learning via Hodge Decomposition (2605.13834).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13834", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.15185", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Quantitative Video World Model Evaluation for Geometric-Consistency", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Quantitative Video World Model Evaluation for Geometric-Consistency (2605.15185).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15185", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.15012", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance (2605.15012).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.15012", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14876", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning (2605.14876).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14876", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14454", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LiSA: Lifelong Safety Adaptation via Conservative Policy Induction", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for LiSA: Lifelong Safety Adaptation via Conservative Policy Induction (2605.14454).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14454", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14323", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Dynamic Latent Routing", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Dynamic Latent Routing (2605.14323).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14323", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.14051", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks (2605.14051).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14051", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12243", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PreScam: A Benchmark for Predicting Scam Progression from Early Conversations", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for PreScam: A Benchmark for Predicting Scam Progression from Early Conversations (2605.12243).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12243", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11459", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models", "date": "2026-05-17", "createdAt": "2026-05-17", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models (2605.11459).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11459", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:Rentoddb/dbsuera", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Rentoddb/dbsuera", "date": "2026-05-26", "createdAt": "2026-05-16", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56727 downloads.", "popularity": {"value": 56727, "label": "downloads"}, "url": "https://huggingface.co/datasets/Rentoddb/dbsuera", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:n<1k"]}
{"id": "paper:arxiv:2605.13779", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MinT: Managed Infrastructure for Training and Serving Millions of LLMs", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "MinT is a managed infrastructure system that enables efficient low-rank adaptation training and serving by keeping base models resident and moving lightweight adapter revisions, scaling across multiple dimensions including large model architectures, reduced...", "popularity": {"value": 219, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13779", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.10616", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image (2605.10616).", "popularity": {"value": 140, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10616", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13724", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation (2605.13724).", "popularity": {"value": 101, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13724", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.13831", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context (2605.13831).", "popularity": {"value": 87, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13831", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.13841", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents (2605.13841).", "popularity": {"value": 64, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13841", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13565", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Qwen-Image-VAE-2.0 Technical Report", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Qwen-Image-VAE-2.0 Technical Report (2605.13565).", "popularity": {"value": 60, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13565", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.12411", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Predicting Decisions of AI Agents from Limited Interaction through Text-Tabular Modeling", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Predicting Decisions of AI Agents from Limited Interaction through Text-Tabular Modeling (2605.12411).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12411", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12587", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking (2605.12587).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12587", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.13062", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling (2605.13062).", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13062", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13511", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Many-Shot CoT-ICL: Making In-Context Learning Truly Learn", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Many-Shot CoT-ICL: Making In-Context Learning Truly Learn (2605.13511).", "popularity": {"value": 32, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13511", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.11550", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The DAWN of World-Action Interactive Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The DAWN of World-Action Interactive Models (2605.11550).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11550", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12964", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Asymmetric Flow Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Asymmetric Flow Models (2605.12964).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12964", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13757", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FrameSkip: Learning from Fewer but More Informative Frames in VLA Training", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FrameSkip: Learning from Fewer but More Informative Frames in VLA Training (2605.13757).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13757", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07865", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "KL for a KL: On-Policy Distillation with Control Variate Baseline", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for KL for a KL: On-Policy Distillation with Control Variate Baseline (2605.07865).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07865", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09942", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HAGE: Harnessing Agentic Memory via RL-Driven Weighted Graph Evolution", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HAGE: Harnessing Agentic Memory via RL-Driven Weighted Graph Evolution (2605.09942).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09942", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12825", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion (2605.12825).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12825", "tags": ["huggingface-papers", "image-generation", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.12004", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning Agentic Policy from Action Guidance", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning Agentic Policy from Action Guidance (2605.12004).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12004", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12684", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty? (2605.12684).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12684", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08518", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Results and Retrospective Analysis of the CODS 2025 AssetOpsBench Challenge", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Results and Retrospective Analysis of the CODS 2025 AssetOpsBench Challenge (2605.08518).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08518", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12975", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation (2605.12975).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12975", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.13542", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation (2605.13542).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13542", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13037", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning (2605.13037).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13037", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11363", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PresentAgent-2: Towards Generalist Multimodal Presentation Agents", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PresentAgent-2: Towards Generalist Multimodal Presentation Agents (2605.11363).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11363", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13775", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RoboEvolve: Co-Evolving Planner-Simulator for Robotic Manipulation with Limited Data", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RoboEvolve: Co-Evolving Planner-Simulator for Robotic Manipulation with Limited Data (2605.13775).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13775", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13050", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Context Training with Active Information Seeking", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Context Training with Active Information Seeking (2605.13050).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13050", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13030", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FeatCal: Feature Calibration for Post-Merging Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FeatCal: Feature Calibration for Post-Merging Models (2605.13030).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.13030", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12913", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Revisiting DAgger in the Era of LLM-Agents", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Revisiting DAgger in the Era of LLM-Agents (2605.12913).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12913", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09433", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs (2605.09433).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09433", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.05806", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Retrieval from Within: An Intrinsic Capability of Attention-Based Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Retrieval from Within: An Intrinsic Capability of Attention-Based Models (2605.05806).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05806", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.10867", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data (2605.10867).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10867", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.10268", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading (2605.10268).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10268", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.14306", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards Self-Evolving Agentic Literature Retrieval", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Towards Self-Evolving Agentic Literature Retrieval (2605.14306).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.14306", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13647", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FlowCompile: An Optimizing Compiler for Structured LLM Workflows", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for FlowCompile: An Optimizing Compiler for Structured LLM Workflows (2605.13647).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.13647", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13481", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents (2605.13481).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.13481", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.13292", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "IndicMedDialog: A Parallel Multi-Turn Medical Dialogue Dataset for Accessible Healthcare in Indic Languages", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for IndicMedDialog: A Parallel Multi-Turn Medical Dialogue Dataset for Accessible Healthcare in Indic Languages (2605.13292).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.13292", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.13087", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Vividh-ASR: A Complexity-Tiered Benchmark and Optimization Dynamics for Robust Indic Speech Recognition", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Vividh-ASR: A Complexity-Tiered Benchmark and Optimization Dynamics for Robust Indic Speech Recognition (2605.13087).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.13087", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12997", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation (2605.12997).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12997", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.12995", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking (2605.12995).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12995", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12925", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation (2605.12925).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12925", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12770", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WriteSAE: Sparse Autoencoders for Recurrent State", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for WriteSAE: Sparse Autoencoders for Recurrent State (2605.12770).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12770", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12733", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Generalist to Specialist Representation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for From Generalist to Specialist Representation (2605.12733).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12733", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12556", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "M2Retinexformer: Multi-Modal Retinexformer for Low-Light Image Enhancement", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for M2Retinexformer: Multi-Modal Retinexformer for Low-Light Image Enhancement (2605.12556).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12556", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.11733", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Position: LLM Inference Should Be Evaluated as Energy-to-Token Production", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Position: LLM Inference Should Be Evaluated as Energy-to-Token Production (2605.11733).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11733", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.11680", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ShapeCodeBench: A Renewable Benchmark for Perception-to-Program Reconstruction of Synthetic Shape Scenes", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for ShapeCodeBench: A Renewable Benchmark for Perception-to-Program Reconstruction of Synthetic Shape Scenes (2605.11680).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11680", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11378", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "An Empirical Study of Automating Agent Evaluation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for An Empirical Study of Automating Agent Evaluation (2605.11378).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11378", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10315", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Active Tabular Augmentation via Policy-Guided Diffusion Inpainting", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Active Tabular Augmentation via Policy-Guided Diffusion Inpainting (2605.10315).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.10315", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.09806", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models (2605.09806).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09806", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.09591", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Pixels to Concepts: Do Segmentation Models Understand What They Segment?", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for From Pixels to Concepts: Do Segmentation Models Understand What They Segment? (2605.09591).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09591", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.08978", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization (2605.08978).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08978", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08737", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Extrapolation Cliff in On-Policy Distillation of Near-Deterministic Structured Outputs", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for The Extrapolation Cliff in On-Policy Distillation of Near-Deterministic Structured Outputs (2605.08737).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08737", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08583", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Source or It Didn't Happen: A Multi-Agent Framework for Citation Hallucination Detection", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Source or It Didn't Happen: A Multi-Agent Framework for Citation Hallucination Detection (2605.08583).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08583", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08557", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MC-RFM: Geometry-Aware Few-Shot Adaptation via Mixed-Curvature Riemannian Flow Matching", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for MC-RFM: Geometry-Aware Few-Shot Adaptation via Mixed-Curvature Riemannian Flow Matching (2605.08557).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08557", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06607", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AI CFD Scientist: Toward Open-Ended Computational Fluid Dynamics Discovery with Physics-Aware AI Agents", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AI CFD Scientist: Toward Open-Ended Computational Fluid Dynamics Discovery with Physics-Aware AI Agents (2605.06607).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.06607", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06206", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Federation of Experts: Communication Efficient Distributed Inference for Large Language Models", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Federation of Experts: Communication Efficient Distributed Inference for Large Language Models (2605.06206).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.06206", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.05704", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety (2605.05704).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.05704", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04651", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FAAST: Forward-Only Associative Learning via Closed-Form Fast Weights for Test-Time Supervised Adaptation", "date": "2026-05-14", "createdAt": "2026-05-14", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for FAAST: Forward-Only Associative Learning via Closed-Form Fast Weights for Test-Time Supervised Adaptation (2605.04651).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.04651", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:Dagonulca/figofigofigofigo", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Dagonulca/figofigofigofigo", "date": "2026-05-14", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 343605 downloads.", "popularity": {"value": 343605, "label": "downloads"}, "url": "https://huggingface.co/datasets/Dagonulca/figofigofigofigo", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:Drakesuper/rodridre", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Drakesuper/rodridre", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 274424 downloads.", "popularity": {"value": 274424, "label": "downloads"}, "url": "https://huggingface.co/datasets/Drakesuper/rodridre", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:MrPigeon345/DoseRAD2026", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "MrPigeon345/DoseRAD2026", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60345 downloads.", "popularity": {"value": 60345, "label": "downloads"}, "url": "https://huggingface.co/datasets/MrPigeon345/DoseRAD2026", "tags": ["challenge", "datasets", "dose-calculation", "license:cc-by-nc-4.0", "radiotherapy", "real-time", "region:us"]}
{"id": "paper:arxiv:2605.12500", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Unified vision-language models treat understanding and generation as integrated processes rather than separate tasks, demonstrating strong performance across multiple multimodal capabilities including image synthesis and action reasoning. Recent large visio...", "popularity": {"value": 191, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12500", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09530", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents (2605.09530).", "popularity": {"value": 147, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09530", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12357", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "δ-mem: Efficient Online Memory for Large Language Models", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for δ-mem: Efficient Online Memory for Large Language Models (2605.12357).", "popularity": {"value": 125, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12357", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.10899", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards (2605.10899).", "popularity": {"value": 78, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10899", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12090", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "World Action Models: The Next Frontier in Embodied AI", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for World Action Models: The Next Frontier in Embodied AI (2605.12090).", "popularity": {"value": 67, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12090", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12178", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics (2605.12178).", "popularity": {"value": 61, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12178", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09131", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments (2605.09131).", "popularity": {"value": 57, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09131", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06546", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Efficient Pre-Training with Token Superposition", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Efficient Pre-Training with Token Superposition (2605.06546).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06546", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.12013", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "L2P: Unlocking Latent Potential for Pixel Generation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for L2P: Unlocking Latent Potential for Pixel Generation (2605.12013).", "popularity": {"value": 36, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12013", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12495", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward (2605.12495).", "popularity": {"value": 35, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12495", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.10780", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization (2605.10780).", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10780", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07237", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Teaching Language Models to Think in Code", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Teaching Language Models to Think in Code (2605.07237).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07237", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12496", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives (2605.12496).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12496", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.12481", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents (2605.12481).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12481", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10832", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents (2605.10832).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10832", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12978", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Useful Memories Become Faulty When Continuously Updated by LLMs", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Useful Memories Become Faulty When Continuously Updated by LLMs (2605.12978).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12978", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12484", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Learning, Fast and Slow: Towards LLMs That Adapt Continually", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Learning, Fast and Slow: Towards LLMs That Adapt Continually (2605.12484).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12484", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12460", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs (2605.12460).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12460", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09998", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Continual Harness: Online Adaptation for Self-Improving Foundation Agents", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Continual Harness: Online Adaptation for Self-Improving Foundation Agents (2605.09998).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09998", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12501", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Covering Human Action Space for Computer Use: Data Synthesis and Benchmark", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Covering Human Action Space for Computer Use: Data Synthesis and Benchmark (2605.12501).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12501", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12070", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction (2605.12070).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12070", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11882", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "On-Policy Self-Evolution via Failure Trajectories for Agentic Safety Alignment", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for On-Policy Self-Evolution via Failure Trajectories for Agentic Safety Alignment (2605.11882).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11882", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.07579", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States (2605.07579).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07579", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.00080", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "World Model for Robot Learning: A Comprehensive Survey", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for World Model for Robot Learning: A Comprehensive Survey (2605.00080).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00080", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06658", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Relit-LiVE: Relight Video by Jointly Learning Environment Video", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Relit-LiVE: Relight Video by Jointly Learning Environment Video (2605.06658).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06658", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.12497", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Web to Pixels: Bringing Agentic Search into Visual Perception", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Web to Pixels: Bringing Agentic Search into Visual Perception (2605.12497).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12497", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09266", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SeePhys Pro: Diagnosing Modality Transfer and Blind-Training Effects in Multimodal RLVR for Physics Reasoning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SeePhys Pro: Diagnosing Modality Transfer and Blind-Training Effects in Multimodal RLVR for Physics Reasoning (2605.09266).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09266", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.05630", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "One Turn Too Late: Response-Aware Defense Against Hidden Malicious Intent in Multi-Turn Dialogue", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for One Turn Too Late: Response-Aware Defense Against Hidden Malicious Intent in Multi-Turn Dialogue (2605.05630).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05630", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.11136", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales (2605.11136).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11136", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12483", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training (2605.12483).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12483", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10977", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks (2605.10977).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10977", "tags": ["embeddings", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08299", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Do not copy and paste! Rewriting strategies for code retrieval", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Do not copy and paste! Rewriting strategies for code retrieval (2605.08299).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08299", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.11711", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Debiased Model-based Representations for Sample-efficient Continuous Control", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Debiased Model-based Representations for Sample-efficient Continuous Control (2605.11711).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11711", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.11011", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models (2605.11011).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.11011", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10365", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values (2605.10365).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10365", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12477", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MEME: Multi-entity & Evolving Memory Evaluation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MEME: Multi-entity & Evolving Memory Evaluation (2605.12477).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12477", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12438", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Causal Language Modeling Detour Improves Encoder Continued Pretraining", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Causal Language Modeling Detour Improves Encoder Continued Pretraining (2605.12438).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12438", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07153", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs (2605.07153).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07153", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.12492", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation (2605.12492).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12492", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.12466", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Solve the Loop: Attractor Models for Language and Reasoning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Solve the Loop: Attractor Models for Language and Reasoning (2605.12466).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.12466", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08504", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models (2605.08504).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08504", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12498", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EgoForce: Forearm-Guided Camera-Space 3D Hand Pose from a Monocular Egocentric Camera", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for EgoForce: Forearm-Guided Camera-Space 3D Hand Pose from a Monocular Egocentric Camera (2605.12498).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12498", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.12493", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues (2605.12493).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12493", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.12474", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reward Hacking in Rubric-Based Reinforcement Learning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Reward Hacking in Rubric-Based Reinforcement Learning (2605.12474).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12474", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12449", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LychSim: A Controllable and Interactive Simulation Framework for Vision Research", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for LychSim: A Controllable and Interactive Simulation Framework for Vision Research (2605.12449).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12449", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.12426", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometric Factual Recall in Transformers", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Geometric Factual Recall in Transformers (2605.12426).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12426", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.12419", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ORBIT: Preserving Foundational Language Capabilities in GenRetrieval via Origin-Regulated Merging", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for ORBIT: Preserving Foundational Language Capabilities in GenRetrieval via Origin-Regulated Merging (2605.12419).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12419", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.12305", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Images in Sentences: Scaling Interleaved Instructions for Unified Visual Generation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Images in Sentences: Scaling Interleaved Instructions for Unified Visual Generation (2605.12305).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12305", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.12119", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MoCam: Unified Novel View Synthesis via Structured Denoising Dynamics", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for MoCam: Unified Novel View Synthesis via Structured Denoising Dynamics (2605.12119).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.12119", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.11696", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WildRelight: A Real-World Benchmark and Physics-Guided Adaptation for Single-Image Relighting", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for WildRelight: A Real-World Benchmark and Physics-Guided Adaptation for Single-Image Relighting (2605.11696).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11696", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11518", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration -- Learning from Cheap, Optimizing Expensive", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration -- Learning from Cheap, Optimizing Expensive (2605.11518).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11518", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11436", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty (2605.11436).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11436", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.11424", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "VidSplat: Gaussian Splatting Reconstruction with Geometry-Guided Video Diffusion Priors", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for VidSplat: Gaussian Splatting Reconstruction with Geometry-Guided Video Diffusion Priors (2605.11424).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11424", "tags": ["huggingface-papers", "image-generation", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.11400", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniPath: Adaptive Coordination of Understanding and Generation for Unified Multimodal Reasoning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for UniPath: Adaptive Coordination of Understanding and Generation for Unified Multimodal Reasoning (2605.11400).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11400", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.11354", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction (2605.11354).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11354", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.11182", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Many Faces of On-Policy Distillation: Pitfalls, Mechanisms, and Fixes", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for The Many Faces of On-Policy Distillation: Pitfalls, Mechanisms, and Fixes (2605.11182).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.11182", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10376", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SleepWalk: A Three-Tier Benchmark for Stress-Testing Instruction-Guided Vision-Language Navigation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for SleepWalk: A Three-Tier Benchmark for Stress-Testing Instruction-Guided Vision-Language Navigation (2605.10376).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.10376", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10267", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs (2605.10267).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.10267", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.10108", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction (2605.10108).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.10108", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09936", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Urban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Urban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception (2605.09936).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09936", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09932", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FocuSFT: Bilevel Optimization for Dilution-Aware Long-Context Fine-Tuning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for FocuSFT: Bilevel Optimization for Dilution-Aware Long-Context Fine-Tuning (2605.09932).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09932", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09539", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems (2605.09539).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09539", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09296", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts (2605.09296).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09296", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.09252", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLM Agents Already Know When to Call Tools -- Even Without Reasoning", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for LLM Agents Already Know When to Call Tools -- Even Without Reasoning (2605.09252).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.09252", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08734", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation (2605.08734).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08734", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08646", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PAAC: Privacy-Aware Agentic Device-Cloud Collaboration", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for PAAC: Privacy-Aware Agentic Device-Cloud Collaboration (2605.08646).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08646", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08626", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Large Language Models over Networks: Collaborative Intelligence under Resource Constraints", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Large Language Models over Networks: Collaborative Intelligence under Resource Constraints (2605.08626).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.08626", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07654", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reliable Chain-of-Thought via Prefix Consistency", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Reliable Chain-of-Thought via Prefix Consistency (2605.07654).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.07654", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07545", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Implicit Preference Alignment for Human Image Animation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for Implicit Preference Alignment for Human Image Animation (2605.07545).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.07545", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.04702", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation (2605.04702).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2605.04702", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2604.27695", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory", "date": "2026-05-13", "createdAt": "2026-05-13", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-01T17:51:08+00:00", "summary": "Hugging Face daily paper entry for EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory (2604.27695).", "popularity": {"value": 0, "label": "seen"}, "url": "https://huggingface.co/papers/2604.27695", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "hf-dataset:Mario123123/en-us-data-with-images-placeholders-removed", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Mario123123/en-us-data-with-images-placeholders-removed", "date": "2026-05-17", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51016 downloads.", "popularity": {"value": 51016, "label": "downloads"}, "url": "https://huggingface.co/datasets/Mario123123/en-us-data-with-images-placeholders-removed", "tags": ["datasets", "modality:image", "region:us"]}
{"id": "paper:arxiv:2605.10730", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Qwen-Image-2.0 Technical Report", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Qwen-Image-2.0 Technical Report (2605.10730).", "popularity": {"value": 110, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10730", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.09063", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs (2605.09063).", "popularity": {"value": 80, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09063", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08735", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation Models", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation Models (2605.08735).", "popularity": {"value": 70, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08735", "tags": ["huggingface-papers", "multimodal", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.09608", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training (2605.09608).", "popularity": {"value": 52, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09608", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10344", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TMAS: Scaling Test-Time Compute via Multi-Agent Synergy", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TMAS: Scaling Test-Time Compute via Multi-Agent Synergy (2605.10344).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10344", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2509.24244", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Model Merging Scaling Laws in Large Language Models", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Model Merging Scaling Laws in Large Language Models (2509.24244).", "popularity": {"value": 44, "label": "upvotes"}, "url": "https://huggingface.co/papers/2509.24244", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10341", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents (2605.10341).", "popularity": {"value": 34, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10341", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.10922", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Pixal3D: Pixel-Aligned 3D Generation from Images", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Pixal3D: Pixel-Aligned 3D Generation from Images (2605.10922).", "popularity": {"value": 33, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10922", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.07465", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SEIF: Self-Evolving Reinforcement Learning for Instruction Following", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SEIF: Self-Evolving Reinforcement Learning for Instruction Following (2605.07465).", "popularity": {"value": 30, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07465", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10434", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors (2605.10434).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10434", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.07721", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models (2605.07721).", "popularity": {"value": 29, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07721", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.09877", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Key-Value Means", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Key-Value Means (2605.09877).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09877", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08354", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria (2605.08354).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08354", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.08985", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLaVA-UHD v4: What Makes Efficient Visual Encoding in MLLMs?", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLaVA-UHD v4: What Makes Efficient Visual Encoding in MLLMs? (2605.08985).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08985", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.05765", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction (2605.05765).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05765", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10781", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rebellious Student: Reversing Teacher Signals for Reasoning Exploration with Self-Distilled RLVR", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rebellious Student: Reversing Teacher Signals for Reasoning Exploration with Self-Distilled RLVR (2605.10781).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10781", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09959", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "G-Zero: Self-Play for Open-Ended Generation from Zero Data", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for G-Zero: Self-Play for Open-Ended Generation from Zero Data (2605.09959).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09959", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10813", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation (2605.10813).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10813", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08513", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Single Neuron Is Sufficient to Bypass Safety Alignment in Large Language Models", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Single Neuron Is Sufficient to Bypass Safety Alignment in Large Language Models (2605.08513).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08513", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10938", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ELF: Embedded Language Flows", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ELF: Embedded Language Flows (2605.10938).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10938", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09196", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RigidFormer: Learning Rigid Dynamics using Transformers", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RigidFormer: Learning Rigid Dynamics using Transformers (2605.09196).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09196", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2604.26326", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control (2604.26326).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.26326", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10923", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning (2605.10923).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10923", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08738", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training (2605.08738).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08738", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09649", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction (2605.09649).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09649", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.08384", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "jina-embeddings-v5-omni: Text-Geometry-Preserving Multimodal Embeddings via Frozen-Tower Composition", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for jina-embeddings-v5-omni: Text-Geometry-Preserving Multimodal Embeddings via Frozen-Tower Composition (2605.08384).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08384", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.10664", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions (2605.10664).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10664", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.10453", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SlimSpec: Low-Rank Draft LM-Head for Accelerated Speculative Decoding", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SlimSpec: Low-Rank Draft LM-Head for Accelerated Speculative Decoding (2605.10453).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10453", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09996", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization (2605.09996).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09996", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.09271", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding (2605.09271).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09271", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08715", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems (2605.08715).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08715", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.10537", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mela: Test-Time Memory Consolidation based on Transformation Hypothesis", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Mela: Test-Time Memory Consolidation based on Transformation Hypothesis (2605.10537).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10537", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09262", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reinforcing Multimodal Reasoning Against Visual Degradation", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Reinforcing Multimodal Reasoning Against Visual Degradation (2605.09262).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09262", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.10468", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Can Muon Fine-tune Adam-Pretrained Models?", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Can Muon Fine-tune Adam-Pretrained Models? (2605.10468).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.10468", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.09269", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification (2605.09269).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.09269", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.08520", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration (2605.08520).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08520", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06788", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Conformal Agent Error Attribution", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Conformal Agent Error Attribution (2605.06788).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06788", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2604.23789", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation", "date": "2026-05-12", "createdAt": "2026-05-12", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation (2604.23789).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.23789", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "github:nexu-io/html-anything", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nexu-io/html-anything", "date": "2026-06-02", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "✨ The agentic HTML editor — your local AI agent writes the HTML, you ship it. 🚀 75 Skills × 9 Surfaces (magazine · deck · poster · XHS / tweet · prototype · data report · Hyperframes) 🛡️ Sandboxed preview · 📤 1-click to WeChat / X / Zhihu / HTML / PNG 🔑 Zer...", "popularity": {"value": 5990, "label": "stars"}, "url": "https://github.com/nexu-io/html-anything", "tags": ["generative-ai", "video-tools"]}
{"id": "hf-dataset:sam-guided-vlas/rs-all-objects", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sam-guided-vlas/rs-all-objects", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 69879 downloads.", "popularity": {"value": 69879, "label": "downloads"}, "url": "https://huggingface.co/datasets/sam-guided-vlas/rs-all-objects", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:3d", "modality:image", "region:us", "size_categories:1k<n<10k"]}
{"id": "hf-dataset:primed63453/en-us-data-done", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "primed63453/en-us-data-done", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56219 downloads.", "popularity": {"value": 56219, "label": "downloads"}, "url": "https://huggingface.co/datasets/primed63453/en-us-data-done", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:100k<n<1m"]}
{"id": "hf-dataset:primed63453/en-us-data-with-images-placeholders-removed", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "primed63453/en-us-data-with-images-placeholders-removed", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48462 downloads.", "popularity": {"value": 48462, "label": "downloads"}, "url": "https://huggingface.co/datasets/primed63453/en-us-data-with-images-placeholders-removed", "tags": ["datasets", "region:us"]}
{"id": "paper:arxiv:2605.06169", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Mean Mode Screaming: Mean--Variance Split Residuals for 1000-Layer Diffusion Transformers", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Deep diffusion transformers face structural instability at extreme depths due to mean-dominated collapse triggered by mean mode screaming, which is mitigated through mean-variance split residuals that maintain stable training while preserving performance. S...", "popularity": {"value": 233, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06169", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2605.08063", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Flow-OPD: On-Policy Distillation for Flow Matching Models", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Flow-OPD: On-Policy Distillation for Flow Matching Models (2605.08063).", "popularity": {"value": 99, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08063", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2512.18181", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation (2512.18181).", "popularity": {"value": 86, "label": "upvotes"}, "url": "https://huggingface.co/papers/2512.18181", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.08083", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling (2605.08083).", "popularity": {"value": 69, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08083", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06139", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex (2605.06139).", "popularity": {"value": 69, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06139", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07177", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents (2605.07177).", "popularity": {"value": 62, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07177", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06747", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HumanNet: Scaling Human-centric Video Learning to One Million Hours", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HumanNet: Scaling Human-centric Video Learning to One Million Hours (2605.06747).", "popularity": {"value": 52, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06747", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.07396", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rubric-based On-policy Distillation", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rubric-based On-policy Distillation (2605.07396).", "popularity": {"value": 41, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07396", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07825", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Anisotropic Modality Align", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Anisotropic Modality Align (2605.07825).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07825", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07748", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TextLDM: Language Modeling with Continuous Latent Diffusion", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TextLDM: Language Modeling with Continuous Latent Diffusion (2605.07748).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07748", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.07755", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking State Tracking in Recurrent Models Through Error Control Dynamics", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking State Tracking in Recurrent Models Through Error Control Dynamics (2605.07755).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07755", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04615", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Retrieval: A Multitask Benchmark and Model for Code Search", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond Retrieval: A Multitask Benchmark and Model for Code Search (2605.04615).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04615", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.00425", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning (2605.00425).", "popularity": {"value": 23, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00425", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06221", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification (2605.06221).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06221", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04808", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "DecodingTrust-Agent Platform (DTap): A Controllable and Interactive Red-Teaming Platform for AI Agents", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for DecodingTrust-Agent Platform (DTap): A Controllable and Interactive Red-Teaming Platform for AI Agents (2605.04808).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04808", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.07850", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MatryoshkaLoRA: Learning Accurate Hierarchical Low-Rank Representations for LLM Fine-Tuning", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MatryoshkaLoRA: Learning Accurate Hierarchical Low-Rank Representations for LLM Fine-Tuning (2605.07850).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07850", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.05997", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for 4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding (2605.05997).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05997", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2511.07328", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training (2511.07328).", "popularity": {"value": 16, "label": "upvotes"}, "url": "https://huggingface.co/papers/2511.07328", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.07075", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ModelLens: Finding the Best for Your Task from Myriads of Models", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ModelLens: Finding the Best for Your Task from Myriads of Models (2605.07075).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07075", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06924", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A^2RD: Agentic Autoregressive Diffusion for Long Video Consistency", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A^2RD: Agentic Autoregressive Diffusion for Long Video Consistency (2605.06924).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06924", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06597", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniSD: Towards a Unified Self-Distillation Framework for Large Language Models", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UniSD: Towards a Unified Self-Distillation Framework for Large Language Models (2605.06597).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06597", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08078", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Normalizing Trajectory Models", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Normalizing Trajectory Models (2605.08078).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08078", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08044", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Fast Byte Latent Transformer", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Fast Byte Latent Transformer (2605.08044).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08044", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08029", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation (2605.08029).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08029", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.07363", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference (2605.07363).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07363", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2602.03473", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts (2602.03473).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2602.03473", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.08043", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation (2605.08043).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08043", "tags": ["huggingface-papers", "image-generation", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.08678", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI (2605.08678).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.08678", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07915", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion (2605.07915).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07915", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.07896", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "What if AI systems weren't chatbots?", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for What if AI systems weren't chatbots? (2605.07896).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07896", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06832", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "IntentGrasp: A Comprehensive Benchmark for Intent Understanding", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for IntentGrasp: A Comprehensive Benchmark for Intent Understanding (2605.06832).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06832", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.03353", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents (2605.03353).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03353", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.07510", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "InterLV-Search: Benchmarking Interleaved Multimodal Agentic Search", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for InterLV-Search: Benchmarking Interleaved Multimodal Agentic Search (2605.07510).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07510", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06628", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation (2605.06628).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06628", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.07394", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BalCapRL: A Balanced Framework for RL-Based MLLM Image Captioning", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for BalCapRL: A Balanced Framework for RL-Based MLLM Image Captioning (2605.07394).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.07394", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.06716", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms (2605.06716).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06716", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06241", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning (2605.06241).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06241", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.05838", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MDN: Parallelizing Stepwise Momentum for Delta Linear Attention", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MDN: Parallelizing Stepwise Momentum for Delta Linear Attention (2605.05838).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05838", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.05781", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Steering Visual Generation in Unified Multimodal Models with Understanding Supervision", "date": "2026-05-11", "createdAt": "2026-05-11", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Steering Visual Generation in Unified Multimodal Models with Understanding Supervision (2605.05781).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05781", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "hf-dataset:preezy02/en-us-data-with-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "preezy02/en-us-data-with-images", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60757 downloads.", "popularity": {"value": 60757, "label": "downloads"}, "url": "https://huggingface.co/datasets/preezy02/en-us-data-with-images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "paper:arxiv:2605.05242", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus Interaction", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus Interaction (2605.05242).", "popularity": {"value": 120, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05242", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06130", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning (2605.06130).", "popularity": {"value": 112, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06130", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06548", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Continuous Latent Diffusion Language Model", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Continuous Latent Diffusion Language Model (2605.06548).", "popularity": {"value": 80, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06548", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.06416", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MiA-Signature: Approximating Global Activation for Long-Context Understanding", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MiA-Signature: Approximating Global Activation for Long-Context Understanding (2605.06416).", "popularity": {"value": 55, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06416", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.04523", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RaguTeam at SemEval-2026 Task 8: Meno and Friends in a Judge-Orchestrated LLM Ensemble for Faithful Multi-Turn Response Generation", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RaguTeam at SemEval-2026 Task 8: Meno and Friends in a Judge-Orchestrated LLM Ensemble for Faithful Multi-Turn Response Generation (2605.04523).", "popularity": {"value": 47, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04523", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2605.06614", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SkillOS: Learning Skill Curation for Self-Evolving Agents", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SkillOS: Learning Skill Curation for Self-Evolving Agents (2605.06614).", "popularity": {"value": 46, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06614", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06222", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When to Trust Imagination: Adaptive Action Execution for World Action Models", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When to Trust Imagination: Adaptive Action Execution for World Action Models (2605.06222).", "popularity": {"value": 42, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06222", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06507", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MARBLE: Multi-Aspect Reward Balance for Diffusion RL", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MARBLE: Multi-Aspect Reward Balance for Diffusion RL (2605.06507).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06507", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.05566", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration (2605.05566).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05566", "tags": ["fine-tuning", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04045", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Audio-Visual Intelligence in Large Foundation Models", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Audio-Visual Intelligence in Large Foundation Models (2605.04045).", "popularity": {"value": 35, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04045", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.06642", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction (2605.06642).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06642", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06376", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Continuous-Time Distribution Matching for Few-Step Diffusion Distillation", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Continuous-Time Distribution Matching for Few-Step Diffusion Distillation (2605.06376).", "popularity": {"value": 26, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06376", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.06651", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AI Co-Mathematician: Accelerating Mathematicians with Agentic AI", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AI Co-Mathematician: Accelerating Mathematicians with Agentic AI (2605.06651).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06651", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06638", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key (2605.06638).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06638", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.05724", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Auto Research with Specialist Agents Develops Effective and Non-Trivial Training Recipes", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Auto Research with Specialist Agents Develops Effective and Non-Trivial Training Recipes (2605.05724).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05724", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06200", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A^2TGPO: Agentic Turn-Group Policy Optimization with Adaptive Turn-level Clipping", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A^2TGPO: Agentic Turn-Group Policy Optimization with Adaptive Turn-level Clipping (2605.06200).", "popularity": {"value": 14, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06200", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.06665", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "UniPool: A Globally Shared Expert Pool for Mixture-of-Experts", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for UniPool: A Globally Shared Expert Pool for Mixture-of-Experts (2605.06665).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06665", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06663", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "EMO: Pretraining Mixture of Experts for Emergent Modularity", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for EMO: Pretraining Mixture of Experts for Emergent Modularity (2605.06663).", "popularity": {"value": 12, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06663", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06216", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TIDE: Every Layer Knows the Token Beneath the Context", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TIDE: Every Layer Knows the Token Beneath the Context (2605.06216).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06216", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06196", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Granularity Axis: A Micro-to-Macro Latent Direction for Social Roles in Language Models", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Granularity Axis: A Micro-to-Macro Latent Direction for Social Roles in Language Models (2605.06196).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06196", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04647", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ReflectDrive-2: Reinforcement-Learning-Aligned Self-Editing for Discrete Diffusion Driving", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ReflectDrive-2: Reinforcement-Learning-Aligned Self-Editing for Discrete Diffusion Driving (2605.04647).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04647", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.04962", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding (2605.04962).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04962", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04451", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RemoteZero: Geospatial Reasoning with Zero Human Annotations", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RemoteZero: Geospatial Reasoning with Zero Human Annotations (2605.04451).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04451", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04956", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "KernelBench-X: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for KernelBench-X: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels (2605.04956).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04956", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04077", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO (2605.04077).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04077", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01640", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Prescriptive Scaling Laws for Data Constrained Training", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Prescriptive Scaling Laws for Data Constrained Training (2605.01640).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01640", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06627", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PianoCoRe: Combined and Refined Piano MIDI Dataset", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PianoCoRe: Combined and Refined Piano MIDI Dataset (2605.06627).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06627", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.06652", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "When No Benchmark Exists: Validating Comparative LLM Safety Scoring Without Ground-Truth Labels", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for When No Benchmark Exists: Validating Comparative LLM Safety Scoring Without Ground-Truth Labels (2605.06652).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.06652", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.05758", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "BioTool: A Comprehensive Tool-Calling Dataset for Enhancing Biomedical Capabilities of Large Language Models", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for BioTool: A Comprehensive Tool-Calling Dataset for Enhancing Biomedical Capabilities of Large Language Models (2605.05758).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05758", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04330", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "The Scaling Properties of Implicit Deductive Reasoning in Transformers", "date": "2026-05-10", "createdAt": "2026-05-10", "sourceUpdatedAt": "2026-05-10", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for The Scaling Properties of Implicit Deductive Reasoning in Transformers (2605.04330).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04330", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:edisonqkj/MultiCities", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "edisonqkj/MultiCities", "date": "2026-05-08", "createdAt": "2026-05-08", "sourceUpdatedAt": "2026-05-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49755 downloads.", "popularity": {"value": 49755, "label": "downloads"}, "url": "https://huggingface.co/datasets/edisonqkj/MultiCities", "tags": ["datasets", "license:other", "modality:image", "region:us", "task_categories:image-to-image"]}
{"id": "hf-dataset:blanchon/opencs2_dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "blanchon/opencs2_dataset", "date": "2026-05-04", "createdAt": "2026-05-08", "sourceUpdatedAt": "2026-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50933 downloads.", "popularity": {"value": 50933, "label": "downloads"}, "url": "https://huggingface.co/datasets/blanchon/opencs2_dataset", "tags": ["audio", "counter-strike-2", "datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:fpvlabs/stera-10m", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fpvlabs/stera-10m", "date": "2026-05-21", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56148 downloads.", "popularity": {"value": 56148, "label": "downloads"}, "url": "https://huggingface.co/datasets/fpvlabs/stera-10m", "tags": ["3d", "4d", "6dof-pose", "arkit", "arxiv:2605.05945", "audio", "captions", "datasets"]}
{"id": "paper:arxiv:2605.03849", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation (2605.03849).", "popularity": {"value": 126, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03849", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.03269", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "RLDX-1 Technical Report", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for RLDX-1 Technical Report (2605.03269).", "popularity": {"value": 125, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03269", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04461", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Stream-T1: Test-Time Scaling for Streaming Video Generation", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Stream-T1: Test-Time Scaling for Streaming Video Generation (2605.04461).", "popularity": {"value": 105, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04461", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.05185", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents (2605.05185).", "popularity": {"value": 101, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05185", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2604.27393", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction (2604.27393).", "popularity": {"value": 77, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.27393", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2604.28196", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation (2604.28196).", "popularity": {"value": 72, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.28196", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.04018", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems (2605.04018).", "popularity": {"value": 40, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04018", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.05163", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World (2605.05163).", "popularity": {"value": 37, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05163", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.05204", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models (2605.05204).", "popularity": {"value": 27, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05204", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.02910", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "CreativityBench: Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for CreativityBench: Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing (2605.02910).", "popularity": {"value": 22, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02910", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04569", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Lightning Unified Video Editing via In-Context Sparse Attention", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Lightning Unified Video Editing via In-Context Sparse Attention (2605.04569).", "popularity": {"value": 18, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04569", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.04128", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation (2605.04128).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04128", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.05662", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity (2605.05662).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.05662", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.00380", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning (2605.00380).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00380", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.03848", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Parameter-Efficient Multi-View Proficiency Estimation: From Discriminative Classification to Generative Feedback", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Parameter-Efficient Multi-View Proficiency Estimation: From Discriminative Classification to Generative Feedback (2605.03848).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03848", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.03395", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music", "date": "2026-05-07", "createdAt": "2026-05-07", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music (2605.03395).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03395", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "hf-dataset:Pthahnix/FoldCloud-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Pthahnix/FoldCloud-Dataset", "date": "2026-05-08", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 76221 downloads.", "popularity": {"value": 76221, "label": "downloads"}, "url": "https://huggingface.co/datasets/Pthahnix/FoldCloud-Dataset", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:blanchon/cs2_dataset_render_part2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "blanchon/cs2_dataset_render_part2", "date": "2026-05-07", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 91566 downloads.", "popularity": {"value": 91566, "label": "downloads"}, "url": "https://huggingface.co/datasets/blanchon/cs2_dataset_render_part2", "tags": ["audio", "counter-strike", "cs2", "datasets", "esports", "hltv", "language:en", "license:cc-by-4.0"]}
{"id": "hf-dataset:Nereusdata/Nereus", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Nereusdata/Nereus", "date": "2026-05-07", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 57770 downloads.", "popularity": {"value": 57770, "label": "downloads"}, "url": "https://huggingface.co/datasets/Nereusdata/Nereus", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:1k<n<10k"]}
{"id": "paper:arxiv:2605.03042", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration (2605.03042).", "popularity": {"value": 124, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03042", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.04036", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories (2605.04036).", "popularity": {"value": 68, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04036", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2604.28123", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Beyond SFT-to-RL: Pre-alignment via Black-Box On-Policy Distillation for Multimodal RL", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Beyond SFT-to-RL: Pre-alignment via Black-Box On-Policy Distillation for Multimodal RL (2604.28123).", "popularity": {"value": 49, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.28123", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2605.00891", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "X2SAM: Any Segmentation in Images and Videos", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for X2SAM: Any Segmentation in Images and Videos (2605.00891).", "popularity": {"value": 25, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00891", "tags": ["huggingface-papers", "paper", "research", "video-generation", "vision"]}
{"id": "paper:arxiv:2605.02396", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HeavySkill: Heavy Thinking as the Inner Skill in Agentic Harness", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HeavySkill: Heavy Thinking as the Inner Skill in Agentic Harness (2605.02396).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02396", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02134", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Video Generation with Predictive Latents", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Video Generation with Predictive Latents (2605.02134).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02134", "tags": ["huggingface-papers", "paper", "research", "video-generation"]}
{"id": "paper:arxiv:2605.04453", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StableI2I: Spotting Unintended Changes in Image-to-Image Transition", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StableI2I: Spotting Unintended Changes in Image-to-Image Transition (2605.04453).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04453", "tags": ["huggingface-papers", "llm", "paper", "research", "vision"]}
{"id": "paper:arxiv:2605.04012", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SymptomAI: Towards a Conversational AI Agent for Everyday Symptom Assessment", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SymptomAI: Towards a Conversational AI Agent for Everyday Symptom Assessment (2605.04012).", "popularity": {"value": 11, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.04012", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.03596", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies (2605.03596).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03596", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02913", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning (2605.02913).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02913", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2411.18966", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors (2411.18966).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2411.18966", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.02904", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "StateSMix: Online Lossless Compression via Mamba State Space Models and Sparse N-gram Context Mixing", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for StateSMix: Online Lossless Compression via Mamba State Space Models and Sparse N-gram Context Mixing (2605.02904).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02904", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.02801", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces (2605.02801).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02801", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.03571", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PatRe: A Full-Stage Office Action and Rebuttal Generation Benchmark for Patent Examination", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PatRe: A Full-Stage Office Action and Rebuttal Generation Benchmark for Patent Examination (2605.03571).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03571", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2604.27488", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO (2604.27488).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.27488", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01717", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "TCDA: Thread-Constrained Discourse-Aware Modeling for Conversational Sentiment Quadruple Analysis", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for TCDA: Thread-Constrained Discourse-Aware Modeling for Conversational Sentiment Quadruple Analysis (2605.01717).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01717", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01466", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion (2605.01466).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01466", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01371", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue (2605.01371).", "popularity": {"value": 6, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01371", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.03941", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "A Benchmark for Interactive World Models with a Unified Action Generation Framework", "date": "2026-05-06", "createdAt": "2026-05-06", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for A Benchmark for Interactive World Models with a Unified Action Generation Framework (2605.03941).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.03941", "tags": ["evaluation", "huggingface-papers", "paper", "research"]}
{"id": "hf-dataset:PrimBench/primbench-results-v3", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "PrimBench/primbench-results-v3", "date": "2026-05-07", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70780 downloads.", "popularity": {"value": 70780, "label": "downloads"}, "url": "https://huggingface.co/datasets/PrimBench/primbench-results-v3", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:100k<n<1m"]}
{"id": "hf-dataset:JackTrum938/ProObjaverse-300K", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "JackTrum938/ProObjaverse-300K", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81827 downloads.", "popularity": {"value": 81827, "label": "downloads"}, "url": "https://huggingface.co/datasets/JackTrum938/ProObjaverse-300K", "tags": ["datasets", "language:en", "license:apache-2.0", "region:us", "size_categories:10k<n<100k", "task_categories:image-to-3d", "task_categories:image-to-image"]}
{"id": "paper:arxiv:2605.02881", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "MolmoAct2: Action Reasoning Models for Real-world Deployment", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "MolmoAct2 presents an open-action reasoning model for robotics that improves upon previous systems through specialized vision-language-model backbones, new datasets, open-weight action tokenizers, architectural redesign for continuous-action prediction, and...", "popularity": {"value": 348, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02881", "tags": ["huggingface-papers", "inference", "paper", "research"]}
{"id": "paper:arxiv:2604.27660", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "From Context to Skills: Can Language Models Learn from Context Skillfully?", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "A self-evolving framework autonomously discovers and refines context-specific skills for language models through a multi-agent self-play loop with Challenger, Reasoner, and Judge components, improving context learning performance without human supervision....", "popularity": {"value": 166, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.27660", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.01428", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Hallucinations Undermine Trust; Metacognition is a Way Forward", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Hallucinations Undermine Trust; Metacognition is a Way Forward (2605.01428).", "popularity": {"value": 24, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01428", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.00814", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs (2605.00814).", "popularity": {"value": 21, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00814", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2604.28075", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling (2604.28075).", "popularity": {"value": 20, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.28075", "tags": ["huggingface-papers", "paper", "research", "small-local"]}
{"id": "paper:arxiv:2605.02661", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "AcademiClaw: When Students Set Challenges for AI Agents", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for AcademiClaw: When Students Set Challenges for AI Agents (2605.02661).", "popularity": {"value": 17, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02661", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.00877", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models (2605.00877).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00877", "tags": ["huggingface-papers", "multimodal", "paper", "research"]}
{"id": "paper:arxiv:2604.27776", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "WindowsWorld: A Process-Centric Benchmark of Autonomous GUI Agents in Professional Cross-Application Environments", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for WindowsWorld: A Process-Centric Benchmark of Autonomous GUI Agents in Professional Cross-Application Environments (2604.27776).", "popularity": {"value": 15, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.27776", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2405.13729", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "ComboStoc: Combinatorial Stochasticity for Diffusion Generative Models", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for ComboStoc: Combinatorial Stochasticity for Diffusion Generative Models (2405.13729).", "popularity": {"value": 13, "label": "upvotes"}, "url": "https://huggingface.co/papers/2405.13729", "tags": ["huggingface-papers", "image-generation", "paper", "research"]}
{"id": "paper:arxiv:2605.02178", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "T^2PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for T^2PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning (2605.02178).", "popularity": {"value": 10, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02178", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02240", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments (2605.02240).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02240", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "paper:arxiv:2605.02222", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Generative Modeling with Orbit-Space Particle Flow Matching", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Generative Modeling with Orbit-Space Particle Flow Matching (2605.02222).", "popularity": {"value": 9, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02222", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01725", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Motion-Aware Caching for Efficient Autoregressive Video Generation", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Motion-Aware Caching for Efficient Autoregressive Video Generation (2605.01725).", "popularity": {"value": 8, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01725", "tags": ["huggingface-papers", "paper", "research", "small-local", "video-generation"]}
{"id": "paper:arxiv:2605.02730", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Perceptual Flow Network for Visually Grounded Reasoning", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Perceptual Flow Network for Visually Grounded Reasoning (2605.02730).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.02730", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.01711", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Linear-Time Global Visual Modeling without Explicit Attention", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Linear-Time Global Visual Modeling without Explicit Attention (2605.01711).", "popularity": {"value": 7, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.01711", "tags": ["huggingface-papers", "llm", "paper", "research"]}
{"id": "paper:arxiv:2605.00529", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation (2605.00529).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2605.00529", "tags": ["huggingface-papers", "paper", "rag", "research"]}
{"id": "paper:arxiv:2604.09408", "source": "Hugging Face Papers", "sourceId": "huggingface-papers", "kind": "paper", "name": "HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help?", "date": "2026-05-05", "createdAt": "2026-05-05", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face daily paper entry for HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help? (2604.09408).", "popularity": {"value": 5, "label": "upvotes"}, "url": "https://huggingface.co/papers/2604.09408", "tags": ["agents", "huggingface-papers", "paper", "research"]}
{"id": "hf-dataset:ruturajchallawar/MAVOS-DD", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ruturajchallawar/MAVOS-DD", "date": "2026-05-04", "createdAt": "2026-05-04", "sourceUpdatedAt": "2026-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52408 downloads.", "popularity": {"value": 52408, "label": "downloads"}, "url": "https://huggingface.co/datasets/ruturajchallawar/MAVOS-DD", "tags": ["arxiv:2505.11109", "datasets", "language:ar", "language:de", "language:en", "language:es", "language:hi", "language:ro"]}
{"id": "hf-dataset:wannaphong/wikipedia-monthly", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "wannaphong/wikipedia-monthly", "date": "2026-05-04", "createdAt": "2026-05-04", "sourceUpdatedAt": "2026-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52074 downloads.", "popularity": {"value": 52074, "label": "downloads"}, "url": "https://huggingface.co/datasets/wannaphong/wikipedia-monthly", "tags": ["100k<n<1m", "10k<n<100k", "10m<n<100m", "1k<n<10k", "1m<n<10m", "datasets", "language:aa", "language:ab"]}
{"id": "hf-dataset:wegrthj/kbcpjv-qi9l-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "wegrthj/kbcpjv-qi9l-data", "date": "2026-06-04", "createdAt": "2026-05-02", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50215 downloads.", "popularity": {"value": 50215, "label": "downloads"}, "url": "https://huggingface.co/datasets/wegrthj/kbcpjv-qi9l-data", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:GokuScraper/seedance-2-prompts-datasets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "GokuScraper/seedance-2-prompts-datasets", "date": "2026-05-14", "createdAt": "2026-05-02", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66031 downloads.", "popularity": {"value": 66031, "label": "downloads"}, "url": "https://huggingface.co/datasets/GokuScraper/seedance-2-prompts-datasets", "tags": ["datasets", "format:json", "language:en", "language:zh", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:pulmo/ncbi-genbank-complete", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "pulmo/ncbi-genbank-complete", "date": "2026-05-14", "createdAt": "2026-05-01", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70993 downloads.", "popularity": {"value": 70993, "label": "downloads"}, "url": "https://huggingface.co/datasets/pulmo/ncbi-genbank-complete", "tags": ["bioinformatics", "biology", "datasets", "dna", "genomics", "language:en", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:huggingworld/ncbi-refseq-complete", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "huggingworld/ncbi-refseq-complete", "date": "2026-05-04", "createdAt": "2026-05-01", "sourceUpdatedAt": "2026-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53209 downloads.", "popularity": {"value": 53209, "label": "downloads"}, "url": "https://huggingface.co/datasets/huggingworld/ncbi-refseq-complete", "tags": ["bioinformatics", "biology", "datasets", "dna", "genomics", "language:en", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:plaume8/terminal-bench-2-leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "plaume8/terminal-bench-2-leaderboard", "date": "2026-04-30", "createdAt": "2026-04-30", "sourceUpdatedAt": "2026-04-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62072 downloads.", "popularity": {"value": 62072, "label": "downloads"}, "url": "https://huggingface.co/datasets/plaume8/terminal-bench-2-leaderboard", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:NuTonic/sat-vl-sft-training-ready-v1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "NuTonic/sat-vl-sft-training-ready-v1", "date": "2026-04-30", "createdAt": "2026-04-30", "sourceUpdatedAt": "2026-04-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50218 downloads.", "popularity": {"value": 50218, "label": "downloads"}, "url": "https://huggingface.co/datasets/NuTonic/sat-vl-sft-training-ready-v1", "tags": ["bounding-boxes", "datasets", "dynamic-world", "format:json", "grounding", "instruction-tuning", "language:en", "library:datasets"]}
{"id": "github:nexu-io/open-design", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nexu-io/open-design", "date": "2026-06-04", "createdAt": "2026-04-28", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🎨 Local-first, open-source Claude Design alternative. 🖥️ Native desktop app. ⚡ 259+ Skills · ✨ 142+ Design Systems 🖼️ Web · desktop · mobile prototypes · slides · images · videos · HyperFrames 📦 Sandboxed preview · HTML/PDF/PPTX/MP4 export 🤖 Claude Code / O...", "popularity": {"value": 58215, "label": "stars"}, "url": "https://github.com/nexu-io/open-design", "tags": ["generative-ai", "video-tools"]}
{"id": "hf-dataset:jasperai/monet", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jasperai/monet", "date": "2026-05-29", "createdAt": "2026-04-28", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 293929 downloads.", "popularity": {"value": 293929, "label": "downloads"}, "url": "https://huggingface.co/datasets/jasperai/monet", "tags": ["arxiv:2605.21272", "captioning", "datasets", "image-text", "language:en", "license:apache-2.0", "multimodal", "region:us"]}
{"id": "github:mrslimslim/gpt-image-canvas", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mrslimslim/gpt-image-canvas", "date": "2026-05-29", "createdAt": "2026-04-28", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Local professional AI canvas built with tldraw.", "popularity": {"value": 595, "label": "stars"}, "url": "https://github.com/mrslimslim/gpt-image-canvas", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:disco-eth/WorldSpeech", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "disco-eth/WorldSpeech", "date": "2026-05-18", "createdAt": "2026-04-28", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 101222 downloads.", "popularity": {"value": 101222, "label": "downloads"}, "url": "https://huggingface.co/datasets/disco-eth/WorldSpeech", "tags": ["arxiv:2605.09167", "asr", "audio", "datasets", "doi:10.57967/hf/8660", "language:af", "language:am", "language:ar"]}
{"id": "hf-dataset:hzxie/DOM", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hzxie/DOM", "date": "2026-04-27", "createdAt": "2026-04-27", "sourceUpdatedAt": "2026-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 111977 downloads.", "popularity": {"value": 111977, "label": "downloads"}, "url": "https://huggingface.co/datasets/hzxie/DOM", "tags": ["arxiv:2601.22153", "datasets", "dynamic", "franka", "lerobot", "license:other", "region:us", "size_categories:100k<n<1m"]}
{"id": "hf-dataset:hugging-science/mmu_legacysurvey_dr10_south_21", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hugging-science/mmu_legacysurvey_dr10_south_21", "date": "2026-06-03", "createdAt": "2026-04-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60700 downloads.", "popularity": {"value": 60700, "label": "downloads"}, "url": "https://huggingface.co/datasets/hugging-science/mmu_legacysurvey_dr10_south_21", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:Collapsecdn/collapsecdn", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Collapsecdn/collapsecdn", "date": "2026-05-27", "createdAt": "2026-04-25", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54292 downloads.", "popularity": {"value": 54292, "label": "downloads"}, "url": "https://huggingface.co/datasets/Collapsecdn/collapsecdn", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:shpklll/OCR-Documents-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "shpklll/OCR-Documents-Dataset", "date": "2026-04-26", "createdAt": "2026-04-25", "sourceUpdatedAt": "2026-04-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 72082 downloads.", "popularity": {"value": 72082, "label": "downloads"}, "url": "https://huggingface.co/datasets/shpklll/OCR-Documents-Dataset", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:willowyll/terminal-bench-2-leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "willowyll/terminal-bench-2-leaderboard", "date": "2026-04-25", "createdAt": "2026-04-25", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56128 downloads.", "popularity": {"value": 56128, "label": "downloads"}, "url": "https://huggingface.co/datasets/willowyll/terminal-bench-2-leaderboard", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:aryaniyaps/terminal-bench-2-leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "aryaniyaps/terminal-bench-2-leaderboard", "date": "2026-04-25", "createdAt": "2026-04-25", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52598 downloads.", "popularity": {"value": 52598, "label": "downloads"}, "url": "https://huggingface.co/datasets/aryaniyaps/terminal-bench-2-leaderboard", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:jeyasuryaur/cricket-data-by-cricsheet", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jeyasuryaur/cricket-data-by-cricsheet", "date": "2026-04-25", "createdAt": "2026-04-24", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 100331 downloads.", "popularity": {"value": 100331, "label": "downloads"}, "url": "https://huggingface.co/datasets/jeyasuryaur/cricket-data-by-cricsheet", "tags": ["datasets", "region:us"]}
{"id": "github:op7418/guizang-ppt-skill", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "op7418/guizang-ppt-skill", "date": "2026-06-02", "createdAt": "2026-04-23", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI-agent Skill for generating polished HTML slide decks: editorial magazine and Swiss layouts, image prompts, social covers, and a WebGL/low-power presentation runtime.", "popularity": {"value": 14742, "label": "stars"}, "url": "https://github.com/op7418/guizang-ppt-skill", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:NuTonic/sat-image-boundingbox-sft-full", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "NuTonic/sat-image-boundingbox-sft-full", "date": "2026-04-23", "createdAt": "2026-04-23", "sourceUpdatedAt": "2026-04-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 116892 downloads.", "popularity": {"value": 116892, "label": "downloads"}, "url": "https://huggingface.co/datasets/NuTonic/sat-image-boundingbox-sft-full", "tags": ["datasets", "earth", "format:json", "geospatial", "land", "land-cover", "language:en", "lfm-vl"]}
{"id": "github:worldwonderer/oh-story-claudecode", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "worldwonderer/oh-story-claudecode", "date": "2026-06-03", "createdAt": "2026-04-22", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "网文/小说写作 skill 包，覆盖长篇与短篇网络小说的扫榜、拆文、写作、去AI味、封面图全流程", "popularity": {"value": 1911, "label": "stars"}, "url": "https://github.com/worldwonderer/oh-story-claudecode", "tags": ["agents", "ai-agent"]}
{"id": "github:wuyoscar/gpt-image2-skill", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "wuyoscar/GPT-Image2-Skill", "date": "2026-05-23", "createdAt": "2026-04-22", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "GPT Image 2 prompt gallery, image prompt library, agentic skill, and CLI for OpenAI image generation/editing", "popularity": {"value": 2622, "label": "stars"}, "url": "https://github.com/wuyoscar/GPT-Image2-Skill", "tags": ["agents", "text-to-image"]}
{"id": "hf-model:deepseek-ai/DeepSeek-V4-Pro", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "deepseek-ai/DeepSeek-V4-Pro", "date": "2026-04-22", "createdAt": "2026-04-22", "sourceUpdatedAt": "2026-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5811046 downloads and tags: transformers, safetensors, deepseek_v4, text-generation.", "popularity": {"value": 5811046, "label": "downloads"}, "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro", "tags": ["conversational", "deepseek_v4", "endpoints_compatible", "eval-results", "license:mit", "llm", "safetensors", "text-generation"]}
{"id": "hf-model:deepseek-ai/DeepSeek-V4-Flash", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "deepseek-ai/DeepSeek-V4-Flash", "date": "2026-04-22", "createdAt": "2026-04-22", "sourceUpdatedAt": "2026-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3542202 downloads and tags: transformers, safetensors, conversational, license:mit.", "popularity": {"value": 3542202, "label": "downloads"}, "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash", "tags": ["8-bit", "conversational", "endpoints_compatible", "eval-results", "license:mit", "llm", "region:us", "safetensors"]}
{"id": "github:esengine/deepseek-reasonix", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "esengine/DeepSeek-Reasonix", "date": "2026-06-04", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.", "popularity": {"value": 17492, "label": "stars"}, "url": "https://github.com/esengine/DeepSeek-Reasonix", "tags": ["agents", "ai-agent"]}
{"id": "github:zafer-liu/data-analysis-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Zafer-Liu/Data-Analysis-Agent", "date": "2026-05-31", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "面向商业分析师的智能数据分析体。Intelligent Data Analysis Agent for Business Analysts.", "popularity": {"value": 1264, "label": "stars"}, "url": "https://github.com/Zafer-Liu/Data-Analysis-Agent", "tags": ["agents", "ai-tools"]}
{"id": "github:conardli/garden-skills", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ConardLi/garden-skills", "date": "2026-05-27", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.", "popularity": {"value": 7222, "label": "stars"}, "url": "https://github.com/ConardLi/garden-skills", "tags": ["rag"]}
{"id": "hf-dataset:PsiBotAI/SynData", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "PsiBotAI/SynData", "date": "2026-05-22", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 178842 downloads.", "popularity": {"value": 178842, "label": "downloads"}, "url": "https://huggingface.co/datasets/PsiBotAI/SynData", "tags": ["datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:cc-by-4.0"]}
{"id": "hf-dataset:vankey/RealText-V2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "vankey/RealText-V2", "date": "2026-05-22", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 61097 downloads.", "popularity": {"value": 61097, "label": "downloads"}, "url": "https://huggingface.co/datasets/vankey/RealText-V2", "tags": ["datasets", "document-analysis", "document-forgery-analysis", "forgery-detection", "format:imagefolder", "language:ar", "language:en", "language:id"]}
{"id": "hf-dataset:adrianmele/computer-use-large", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "adrianmele/computer-use-large", "date": "2026-04-21", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-04-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 99847 downloads.", "popularity": {"value": 99847, "label": "downloads"}, "url": "https://huggingface.co/datasets/adrianmele/computer-use-large", "tags": ["computer-use", "datasets", "desktop", "gui", "language:en", "license:cc-by-4.0", "region:us", "screen-recording"]}
{"id": "hf-dataset:Whoisjutanlee/2.1tbofdata", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Whoisjutanlee/2.1tbofdata", "date": "2026-04-21", "createdAt": "2026-04-21", "sourceUpdatedAt": "2026-04-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71254 downloads.", "popularity": {"value": 71254, "label": "downloads"}, "url": "https://huggingface.co/datasets/Whoisjutanlee/2.1tbofdata", "tags": ["arxiv:2510.23763", "datasets", "embodied", "language:en", "license:cc-by-nc-4.0", "omni", "region:us", "robotics"]}
{"id": "github:cosmicstack-labs/mercury-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "cosmicstack-labs/mercury-agent", "date": "2026-06-02", "createdAt": "2026-04-20", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Soul-driven AI agent with permission-hardened tools, token budgets, and multi-channel access. Runs 24/7 from CLI or Telegram.", "popularity": {"value": 2538, "label": "stars"}, "url": "https://github.com/cosmicstack-labs/mercury-agent", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:PeakStars/Math-Instruct", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "PeakStars/Math-Instruct", "date": "2026-04-20", "createdAt": "2026-04-20", "sourceUpdatedAt": "2026-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 217693 downloads.", "popularity": {"value": 217693, "label": "downloads"}, "url": "https://huggingface.co/datasets/PeakStars/Math-Instruct", "tags": ["datasets", "format:optimized-parquet", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular"]}
{"id": "hf-dataset:Dhruv2mars/terminal-bench-2-leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Dhruv2mars/terminal-bench-2-leaderboard", "date": "2026-04-20", "createdAt": "2026-04-20", "sourceUpdatedAt": "2026-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 64751 downloads.", "popularity": {"value": 64751, "label": "downloads"}, "url": "https://huggingface.co/datasets/Dhruv2mars/terminal-bench-2-leaderboard", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:dirac-run/terminal-bench-2-leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "dirac-run/terminal-bench-2-leaderboard", "date": "2026-04-19", "createdAt": "2026-04-19", "sourceUpdatedAt": "2026-04-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53381 downloads.", "popularity": {"value": 53381, "label": "downloads"}, "url": "https://huggingface.co/datasets/dirac-run/terminal-bench-2-leaderboard", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "github:evolinkai/awesome-gpt-image-2-api-and-prompts", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EvoLinkAI/awesome-gpt-image-2-API-and-Prompts", "date": "2026-06-02", "createdAt": "2026-04-18", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "GPT-Image-2 API and Prompts", "popularity": {"value": 15941, "label": "stars"}, "url": "https://github.com/EvoLinkAI/awesome-gpt-image-2-API-and-Prompts", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:YijingGuo/PanoCity", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "YijingGuo/PanoCity", "date": "2026-04-19", "createdAt": "2026-04-18", "sourceUpdatedAt": "2026-04-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 119946 downloads.", "popularity": {"value": 119946, "label": "downloads"}, "url": "https://huggingface.co/datasets/YijingGuo/PanoCity", "tags": ["aerial", "arxiv:2603.17571", "datasets", "depth", "format:imagefolder", "language:en", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:YouthZestLin/OccTrack360", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "YouthZestLin/OccTrack360", "date": "2026-06-04", "createdAt": "2026-04-17", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 68102 downloads.", "popularity": {"value": 68102, "label": "downloads"}, "url": "https://huggingface.co/datasets/YouthZestLin/OccTrack360", "tags": ["datasets", "region:us"]}
{"id": "github:browser-use/browser-harness", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "browser-use/browser-harness", "date": "2026-05-20", "createdAt": "2026-04-17", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Browser Harness | Self-healing harness that enables LLMs to complete any task.", "popularity": {"value": 14309, "label": "stars"}, "url": "https://github.com/browser-use/browser-harness", "tags": ["agents", "ai-agent"]}
{"id": "github:ciembor/agent-rules-books", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ciembor/agent-rules-books", "date": "2026-05-22", "createdAt": "2026-04-16", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AGENTS.md rules / skills for AI coding agents: Codex, Cursor & Claude Code. Inspired by Clean Code, Refactoring, DDD, Clean Architecture and DDIA programming books.", "popularity": {"value": 1736, "label": "stars"}, "url": "https://github.com/ciembor/agent-rules-books", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:hamza-adnan/visual_distracting_metaworld_with_masks", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hamza-adnan/visual_distracting_metaworld_with_masks", "date": "2026-04-28", "createdAt": "2026-04-16", "sourceUpdatedAt": "2026-04-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49059 downloads.", "popularity": {"value": 49059, "label": "downloads"}, "url": "https://huggingface.co/datasets/hamza-adnan/visual_distracting_metaworld_with_masks", "tags": ["datasets", "format:optimized-parquet", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:image"]}
{"id": "hf-dataset:hku-mip/cbct_projection", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hku-mip/cbct_projection", "date": "2026-05-04", "createdAt": "2026-04-15", "sourceUpdatedAt": "2026-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55491 downloads.", "popularity": {"value": 55491, "label": "downloads"}, "url": "https://huggingface.co/datasets/hku-mip/cbct_projection", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "hf-dataset:google/RSRCC", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google/RSRCC", "date": "2026-04-23", "createdAt": "2026-04-15", "sourceUpdatedAt": "2026-04-23", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46671 downloads.", "popularity": {"value": 46671, "label": "downloads"}, "url": "https://huggingface.co/datasets/google/RSRCC", "tags": ["arxiv:2604.20623", "change-detection", "datasets", "format:imagefolder", "geospatial", "image", "language:en", "library:datasets"]}
{"id": "hf-dataset:kapilrao/SEC-EDGAR", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "kapilrao/SEC-EDGAR", "date": "2026-04-15", "createdAt": "2026-04-15", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56314 downloads.", "popularity": {"value": 56314, "label": "downloads"}, "url": "https://huggingface.co/datasets/kapilrao/SEC-EDGAR", "tags": ["datasets", "edgar", "finance", "language:en", "license:apache-2.0", "region:us", "sec", "size_categories:1m<n<10m"]}
{"id": "hf-dataset:novcor/CADS-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "novcor/CADS-dataset", "date": "2026-04-15", "createdAt": "2026-04-15", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52825 downloads.", "popularity": {"value": 52825, "label": "downloads"}, "url": "https://huggingface.co/datasets/novcor/CADS-dataset", "tags": ["3d", "anatomy", "arxiv:2507.22953", "ct", "datasets", "format:csv", "image", "library:datasets"]}
{"id": "hf-dataset:YUJIAXIE/jiefangjunbao", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "YUJIAXIE/jiefangjunbao", "date": "2026-04-14", "createdAt": "2026-04-14", "sourceUpdatedAt": "2026-04-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50438 downloads.", "popularity": {"value": 50438, "label": "downloads"}, "url": "https://huggingface.co/datasets/YUJIAXIE/jiefangjunbao", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:axisrobotics/Franka-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "axisrobotics/Franka-Dataset", "date": "2026-05-30", "createdAt": "2026-04-13", "sourceUpdatedAt": "2026-05-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63532 downloads.", "popularity": {"value": 63532, "label": "downloads"}, "url": "https://huggingface.co/datasets/axisrobotics/Franka-Dataset", "tags": ["datasets", "region:us"]}
{"id": "github:mouseww/anything-analyzer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Mouseww/anything-analyzer", "date": "2026-06-03", "createdAt": "2026-04-12", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "全能协议分析工具：浏览器抓包 + MITM 代理 + 指纹伪装 + AI 分析 + MCP Server 无缝对接 AI Agent/IDE   |  All-in-one protocol analysis toolkit — built-in browser capture, MITM proxy, JS hooks, fingerprint spoofing, AI analysis & MCP server for agent integration", "popularity": {"value": 2797, "label": "stars"}, "url": "https://github.com/Mouseww/anything-analyzer", "tags": ["agents", "ai-tools"]}
{"id": "github:lucasrosati/claude-code-memory-setup", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lucasrosati/claude-code-memory-setup", "date": "2026-06-01", "createdAt": "2026-04-12", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Up to 71.5x fewer tokens per session on Claude Code with Obsidian + Graphify. Persistent memory, codebase knowledge graphs, and chat import pipeline. 🇧🇷 PT-BR included.", "popularity": {"value": 733, "label": "stars"}, "url": "https://github.com/lucasrosati/claude-code-memory-setup", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:apple/DFNDR-2B", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "apple/DFNDR-2B", "date": "2026-05-22", "createdAt": "2026-04-12", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 86329 downloads.", "popularity": {"value": 86329, "label": "downloads"}, "url": "https://huggingface.co/datasets/apple/DFNDR-2B", "tags": ["arxiv:2309.17425", "arxiv:2311.17049", "arxiv:2508.20691", "datasets", "language:en", "license:cc-by-nc-nd-4.0", "region:us", "size_categories:1b<n<10b"]}
{"id": "github:dominikmartn/hue", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dominikmartn/hue", "date": "2026-04-17", "createdAt": "2026-04-12", "sourceUpdatedAt": "2026-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "open-source skill that learns any brand and turns it into a complete design system. works on claude code and codex. install once, every UI your assistant builds matches your brand.", "popularity": {"value": 672, "label": "stars"}, "url": "https://github.com/dominikmartn/hue", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:Dragonegg2026/banned-historical-archives", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Dragonegg2026/banned-historical-archives", "date": "2026-04-12", "createdAt": "2026-04-12", "sourceUpdatedAt": "2026-04-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51305 downloads.", "popularity": {"value": 51305, "label": "downloads"}, "url": "https://huggingface.co/datasets/Dragonegg2026/banned-historical-archives", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "github:ekkolearnai/hermes-web-ui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EKKOLearnAI/hermes-web-ui", "date": "2026-06-04", "createdAt": "2026-04-11", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics", "popularity": {"value": 7199, "label": "stars"}, "url": "https://github.com/EKKOLearnAI/hermes-web-ui", "tags": ["agents", "ai-agent"]}
{"id": "github:run-llama/parsebench", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "run-llama/ParseBench", "date": "2026-06-01", "createdAt": "2026-04-10", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ParseBench - A Document Parsing Benchmark for AI Agents", "popularity": {"value": 474, "label": "stars"}, "url": "https://github.com/run-llama/ParseBench", "tags": ["agents", "evaluation"]}
{"id": "hf-dataset:jdopensource/JoyAI-Image-OpenSpatial", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jdopensource/JoyAI-Image-OpenSpatial", "date": "2026-04-15", "createdAt": "2026-04-10", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66829 downloads.", "popularity": {"value": 66829, "label": "downloads"}, "url": "https://huggingface.co/datasets/jdopensource/JoyAI-Image-OpenSpatial", "tags": ["3d-grounding", "3d-vision", "datasets", "depth-estimation", "format:parquet", "language:en", "library:dask", "library:datasets"]}
{"id": "hf-dataset:vctvct321/pointo", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "vctvct321/pointo", "date": "2026-06-04", "createdAt": "2026-04-09", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70647 downloads.", "popularity": {"value": 70647, "label": "downloads"}, "url": "https://huggingface.co/datasets/vctvct321/pointo", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:llamaindex/ParseBench", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "llamaindex/ParseBench", "date": "2026-04-19", "createdAt": "2026-04-09", "sourceUpdatedAt": "2026-04-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53737 downloads.", "popularity": {"value": 53737, "label": "downloads"}, "url": "https://huggingface.co/datasets/llamaindex/ParseBench", "tags": ["arxiv:2604.08538", "benchmark", "benchmark:eval-yaml", "benchmark:official", "charts", "datasets", "document-parsing", "evaluation"]}
{"id": "hf-dataset:datdong2004/amazonNew-cleaned", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "datdong2004/amazonNew-cleaned", "date": "2026-04-09", "createdAt": "2026-04-09", "sourceUpdatedAt": "2026-04-09", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47630 downloads.", "popularity": {"value": 47630, "label": "downloads"}, "url": "https://huggingface.co/datasets/datdong2004/amazonNew-cleaned", "tags": ["datasets", "region:us"]}
{"id": "github:google/agents-cli", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "google/agents-cli", "date": "2026-06-01", "createdAt": "2026-04-08", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.", "popularity": {"value": 2696, "label": "stars"}, "url": "https://github.com/google/agents-cli", "tags": ["agents", "generative-ai"]}
{"id": "hf-dataset:zjunlp/OceanCorpus", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "zjunlp/OceanCorpus", "date": "2026-05-07", "createdAt": "2026-04-08", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53824 downloads.", "popularity": {"value": 53824, "label": "downloads"}, "url": "https://huggingface.co/datasets/zjunlp/OceanCorpus", "tags": ["datasets", "format:imagefolder", "instruction-tuning", "knowledge-injection", "language:en", "library:datasets", "library:mlcroissant", "license:mit"]}
{"id": "hf-dataset:nvidia/OCR-Synthetic-Multilingual-v1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/OCR-Synthetic-Multilingual-v1", "date": "2026-04-20", "createdAt": "2026-04-08", "sourceUpdatedAt": "2026-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 435184 downloads.", "popularity": {"value": 435184, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/OCR-Synthetic-Multilingual-v1", "tags": ["datasets", "hdf5", "language:en", "language:ja", "language:ko", "language:ru", "language:zh", "license:cc-by-4.0"]}
{"id": "hf-dataset:timchen0618/bcp-traj-ext-formatted-v1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "timchen0618/bcp-traj-ext-formatted-v1", "date": "2026-04-08", "createdAt": "2026-04-08", "sourceUpdatedAt": "2026-04-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 138493 downloads.", "popularity": {"value": 138493, "label": "downloads"}, "url": "https://huggingface.co/datasets/timchen0618/bcp-traj-ext-formatted-v1", "tags": ["bcp", "browsecomp-plus", "datasets", "format:optimized-parquet", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "github:tencentcloud/tencentdb-agent-memory", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "TencentCloud/TencentDB-Agent-Memory", "date": "2026-06-02", "createdAt": "2026-04-07", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.", "popularity": {"value": 4720, "label": "stars"}, "url": "https://github.com/TencentCloud/TencentDB-Agent-Memory", "tags": ["agents", "ai-agent"]}
{"id": "github:tencent/tencentdb-agent-memory", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Tencent/TencentDB-Agent-Memory", "date": "2026-06-01", "createdAt": "2026-04-07", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.", "popularity": {"value": 4534, "label": "stars"}, "url": "https://github.com/Tencent/TencentDB-Agent-Memory", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:asoorazam/forgetest", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "asoorazam/forgetest", "date": "2026-04-07", "createdAt": "2026-04-07", "sourceUpdatedAt": "2026-04-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59634 downloads.", "popularity": {"value": 59634, "label": "downloads"}, "url": "https://huggingface.co/datasets/asoorazam/forgetest", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:hungsmoie/heo3x", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hungsmoie/heo3x", "date": "2026-06-01", "createdAt": "2026-04-06", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59330 downloads.", "popularity": {"value": 59330, "label": "downloads"}, "url": "https://huggingface.co/datasets/hungsmoie/heo3x", "tags": ["datasets", "library:datasets", "library:mlcroissant", "license:apache-2.0", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:apararti/betty-dota2-canonical-v1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "apararti/betty-dota2-canonical-v1", "date": "2026-04-12", "createdAt": "2026-04-06", "sourceUpdatedAt": "2026-04-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 61031 downloads.", "popularity": {"value": 61031, "label": "downloads"}, "url": "https://huggingface.co/datasets/apararti/betty-dota2-canonical-v1", "tags": ["datasets", "region:us"]}
{"id": "github:mempalace/mempalace", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MemPalace/mempalace", "date": "2026-06-03", "createdAt": "2026-04-05", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The best-benchmarked open-source AI memory system. And it's free.", "popularity": {"value": 53382, "label": "stars"}, "url": "https://github.com/MemPalace/mempalace", "tags": ["evaluation", "llm"]}
{"id": "github:mm7894215/tokentracker", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mm7894215/TokenTracker", "date": "2026-06-03", "createdAt": "2026-04-05", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Track token usage across 22 AI coding tools (Claude Code, Codex, Cursor, Gemini, Roo Code, Zed Agent, Goose, and more) — local-first, zero-config, with a beautiful dashboard, native macOS menu bar app, and 4 desktop widgets.", "popularity": {"value": 642, "label": "stars"}, "url": "https://github.com/mm7894215/TokenTracker", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:InternRobotics/EBench-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "InternRobotics/EBench-Dataset", "date": "2026-05-23", "createdAt": "2026-04-05", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 210087 downloads.", "popularity": {"value": 210087, "label": "downloads"}, "url": "https://huggingface.co/datasets/InternRobotics/EBench-Dataset", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:10k<n<100k"]}
{"id": "hf-dataset:shaharec/deepef-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "shaharec/deepef-data", "date": "2026-04-09", "createdAt": "2026-04-05", "sourceUpdatedAt": "2026-04-09", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47266 downloads.", "popularity": {"value": 47266, "label": "downloads"}, "url": "https://huggingface.co/datasets/shaharec/deepef-data", "tags": ["datasets", "license:mit", "protein", "region:us", "structural-biology", "thermodynamic-stability"]}
{"id": "hf-dataset:hosam12kalad/OmniAction", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hosam12kalad/OmniAction", "date": "2026-04-05", "createdAt": "2026-04-05", "sourceUpdatedAt": "2026-04-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 77600 downloads.", "popularity": {"value": 77600, "label": "downloads"}, "url": "https://huggingface.co/datasets/hosam12kalad/OmniAction", "tags": ["arxiv:2510.23763", "datasets", "embodied", "language:en", "license:cc-by-nc-4.0", "omni", "region:us", "robotics"]}
{"id": "github:santifer/career-ops", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "santifer/career-ops", "date": "2026-06-03", "createdAt": "2026-04-04", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.", "popularity": {"value": 48545, "label": "stars"}, "url": "https://github.com/santifer/career-ops", "tags": ["agents", "ai-agent"]}
{"id": "github:juliusbrussee/caveman", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "JuliusBrussee/caveman", "date": "2026-05-20", "createdAt": "2026-04-04", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman", "popularity": {"value": 68413, "label": "stars"}, "url": "https://github.com/JuliusBrussee/caveman", "tags": ["llm", "tools"]}
{"id": "github:safishamsi/graphify", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "safishamsi/graphify", "date": "2026-06-03", "createdAt": "2026-04-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastruc...", "popularity": {"value": 58932, "label": "stars"}, "url": "https://github.com/safishamsi/graphify", "tags": ["rag", "video-tools"]}
{"id": "hf-dataset:Williamsanderson/MedQA-Darija-MultiLingual", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Williamsanderson/MedQA-Darija-MultiLingual", "date": "2026-05-06", "createdAt": "2026-04-03", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56828 downloads.", "popularity": {"value": 56828, "label": "downloads"}, "url": "https://huggingface.co/datasets/Williamsanderson/MedQA-Darija-MultiLingual", "tags": ["audio", "darija", "datasets", "format:parquet", "healthcare", "language:ar", "language:en", "language:fr"]}
{"id": "hf-dataset:ryanontheinside/demucs-stems-fma-jamendo", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ryanontheinside/demucs-stems-fma-jamendo", "date": "2026-04-06", "createdAt": "2026-04-03", "sourceUpdatedAt": "2026-04-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62193 downloads.", "popularity": {"value": 62193, "label": "downloads"}, "url": "https://huggingface.co/datasets/ryanontheinside/demucs-stems-fma-jamendo", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:echodict/KakologArchives_duplicate", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "echodict/KakologArchives_duplicate", "date": "2026-04-03", "createdAt": "2026-04-03", "sourceUpdatedAt": "2026-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60412 downloads.", "popularity": {"value": 60412, "label": "downloads"}, "url": "https://huggingface.co/datasets/echodict/KakologArchives_duplicate", "tags": ["datasets", "language:ja", "license:mit", "region:us", "task_categories:text-classification"]}
{"id": "hf-dataset:lmarena-ai/leaderboard-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lmarena-ai/leaderboard-dataset", "date": "2026-06-03", "createdAt": "2026-04-02", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50338 downloads.", "popularity": {"value": 50338, "label": "downloads"}, "url": "https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:cc-by-4.0", "modality:tabular"]}
{"id": "github:thinkwatchproject/thinkwatch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ThinkWatchProject/ThinkWatch", "date": "2026-05-27", "createdAt": "2026-04-02", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Enterprise AI bastion host for secure AI API and MCP access, with unified proxying, RBAC, audit logs, rate limiting, and cost tracking across OpenAI, Anthropic, Gemini, and self-hosted LLMs.", "popularity": {"value": 1007, "label": "stars"}, "url": "https://github.com/ThinkWatchProject/ThinkWatch", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:hkuds/vibe-trading", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HKUDS/Vibe-Trading", "date": "2026-06-04", "createdAt": "2026-04-01", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "\"Vibe-Trading: Your Personal Trading Agent\"", "popularity": {"value": 10045, "label": "stars"}, "url": "https://github.com/HKUDS/Vibe-Trading", "tags": ["agents", "ai-agent"]}
{"id": "github:gitlawb/openclaude", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Gitlawb/openclaude", "date": "2026-06-03", "createdAt": "2026-04-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "runs anywhere. uses anything", "popularity": {"value": 28288, "label": "stars"}, "url": "https://github.com/Gitlawb/openclaude", "tags": ["agents", "ai-agent"]}
{"id": "github:repowise-dev/claude-code-prompts", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "repowise-dev/claude-code-prompts", "date": "2026-05-11", "createdAt": "2026-04-01", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Independently authored prompt templates for AI coding agents — system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Informed by studying Claude Code.", "popularity": {"value": 1076, "label": "stars"}, "url": "https://github.com/repowise-dev/claude-code-prompts", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:ayuo/hd_tmp", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ayuo/hd_tmp", "date": "2026-04-11", "createdAt": "2026-04-01", "sourceUpdatedAt": "2026-04-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1495027 downloads.", "popularity": {"value": 1495027, "label": "downloads"}, "url": "https://huggingface.co/datasets/ayuo/hd_tmp", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:AntoineGuedon/FlowerTinyImageDataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AntoineGuedon/FlowerTinyImageDataset", "date": "2026-04-04", "createdAt": "2026-04-01", "sourceUpdatedAt": "2026-04-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56332 downloads.", "popularity": {"value": 56332, "label": "downloads"}, "url": "https://huggingface.co/datasets/AntoineGuedon/FlowerTinyImageDataset", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:KAKA22/SpreadsheetBench-v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "KAKA22/SpreadsheetBench-v2", "date": "2026-06-03", "createdAt": "2026-03-31", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54995 downloads.", "popularity": {"value": 54995, "label": "downloads"}, "url": "https://huggingface.co/datasets/KAKA22/SpreadsheetBench-v2", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:yaojingang/yao-meta-skill", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "yaojingang/yao-meta-skill", "date": "2026-05-20", "createdAt": "2026-03-31", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "YAO = Yielding AI Outcomes. A rigorous engineering, evaluation, governance, and portability system for reusable agent skills.", "popularity": {"value": 419, "label": "stars"}, "url": "https://github.com/yaojingang/yao-meta-skill", "tags": ["agents", "evaluation"]}
{"id": "github:windy3f3f3f3f/how-claude-code-works", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Windy3f3f3f3f/how-claude-code-works", "date": "2026-05-05", "createdAt": "2026-03-31", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Deep dive into Claude Code internals — architecture, agent loop, context engineering, and more. / 深入解析 Claude Code 源码：架构、Agent 循环、上下文工程、工具系统等", "popularity": {"value": 2552, "label": "stars"}, "url": "https://github.com/Windy3f3f3f3f/how-claude-code-works", "tags": ["agents", "ai-agent"]}
{"id": "github:lintsinghua/claude-code-book", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lintsinghua/claude-code-book", "date": "2026-04-06", "createdAt": "2026-03-31", "sourceUpdatedAt": "2026-04-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "《御舆：解码 Agent Harness》42万字拆解 AI Agent 的Harness骨架与神经 —— Claude Code 架构深度剖析，15 章从对话循环到构建你自己的 Agent Harness。在线阅读网站：", "popularity": {"value": 3538, "label": "stars"}, "url": "https://github.com/lintsinghua/claude-code-book", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:rad1d1m123/OmniAction", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rad1d1m123/OmniAction", "date": "2026-03-31", "createdAt": "2026-03-31", "sourceUpdatedAt": "2026-03-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 100562 downloads.", "popularity": {"value": 100562, "label": "downloads"}, "url": "https://huggingface.co/datasets/rad1d1m123/OmniAction", "tags": ["arxiv:2510.23763", "datasets", "embodied", "language:en", "license:cc-by-nc-4.0", "omni", "region:us", "robotics"]}
{"id": "github:blazeup-ai/observal", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "BlazeUp-AI/Observal", "date": "2026-06-03", "createdAt": "2026-03-30", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Observal is a unified platform for agent distribution, observability and insights.", "popularity": {"value": 1960, "label": "stars"}, "url": "https://github.com/BlazeUp-AI/Observal", "tags": ["agents", "llmops"]}
{"id": "hf-model:k2-fsa/OmniVoice", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "k2-fsa/OmniVoice", "date": "2026-03-30", "createdAt": "2026-03-30", "sourceUpdatedAt": "2026-03-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2513577 downloads and tags: omnivoice, safetensors, zero-shot, multilingual.", "popularity": {"value": 2513577, "label": "downloads"}, "url": "https://huggingface.co/k2-fsa/OmniVoice", "tags": ["aae", "audio", "multilingual", "omnivoice", "safetensors", "text-to-speech", "voice-cloning", "voice-design"]}
{"id": "github:walkinglabs/learn-harness-engineering", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "walkinglabs/learn-harness-engineering", "date": "2026-06-04", "createdAt": "2026-03-29", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Harness engineering official style beginner tutorial, from 0 to 1", "popularity": {"value": 7606, "label": "stars"}, "url": "https://github.com/walkinglabs/learn-harness-engineering", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:Tyl3rDrden/ivrit-knesset-shards-v5", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Tyl3rDrden/ivrit-knesset-shards-v5", "date": "2026-03-30", "createdAt": "2026-03-29", "sourceUpdatedAt": "2026-03-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63258 downloads.", "popularity": {"value": 63258, "label": "downloads"}, "url": "https://huggingface.co/datasets/Tyl3rDrden/ivrit-knesset-shards-v5", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:Perry233/astrovision-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Perry233/astrovision-data", "date": "2026-03-29", "createdAt": "2026-03-29", "sourceUpdatedAt": "2026-03-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 79564 downloads.", "popularity": {"value": 79564, "label": "downloads"}, "url": "https://huggingface.co/datasets/Perry233/astrovision-data", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:sini-21/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sini-21/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "date": "2026-03-29", "createdAt": "2026-03-29", "sourceUpdatedAt": "2026-03-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 69484 downloads.", "popularity": {"value": 69484, "label": "downloads"}, "url": "https://huggingface.co/datasets/sini-21/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "tags": ["datasets", "license:cc-by-4.0", "region:us", "robotics", "task_categories:robotics"]}
{"id": "github:bitterbot-ai/bitterbot-desktop", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Bitterbot-AI/bitterbot-desktop", "date": "2026-06-03", "createdAt": "2026-03-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A local-first AI agent with persistent memory, emotional intelligence, and a peer-to-peer skills economy.", "popularity": {"value": 2168, "label": "stars"}, "url": "https://github.com/Bitterbot-AI/bitterbot-desktop", "tags": ["agents", "ai-agent"]}
{"id": "github:railly/agentfiles", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Railly/agentfiles", "date": "2026-05-17", "createdAt": "2026-03-28", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Browse, create, and edit AI agent files across Claude Code, Cursor, Codex, and 13+ tools — from Obsidian.", "popularity": {"value": 585, "label": "stars"}, "url": "https://github.com/Railly/agentfiles", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:tayoliang/myself", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tayoliang/myself", "date": "2026-04-25", "createdAt": "2026-03-28", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63939 downloads.", "popularity": {"value": 63939, "label": "downloads"}, "url": "https://huggingface.co/datasets/tayoliang/myself", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:open-index/open-github", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "open-index/open-github", "date": "2026-04-09", "createdAt": "2026-03-27", "sourceUpdatedAt": "2026-04-09", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 58418 downloads.", "popularity": {"value": 58418, "label": "downloads"}, "url": "https://huggingface.co/datasets/open-index/open-github", "tags": ["code", "datasets", "events", "format:parquet", "gharchive", "github", "language:en", "language:mul"]}
{"id": "github:wiltodelta/remove-ai-watermarks", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "wiltodelta/remove-ai-watermarks", "date": "2026-06-04", "createdAt": "2026-03-25", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "CLI and Python library to strip visible and invisible AI watermarks and provenance metadata (SynthID, C2PA, EXIF/XMP \"Made with AI\", Gemini sparkle) from AI-generated images", "popularity": {"value": 2890, "label": "stars"}, "url": "https://github.com/wiltodelta/remove-ai-watermarks", "tags": ["developer-tools", "generative-ai"]}
{"id": "github:adminlove520/ai-account-toolkit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "adminlove520/AI-Account-Toolkit", "date": "2026-06-03", "createdAt": "2026-03-25", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI 账号注册与管理一站式工具集 | ChatGPT, Claude, Gemini, Codex, Cursor, Grok 批量注册、Token 管理、临时邮箱服务", "popularity": {"value": 825, "label": "stars"}, "url": "https://github.com/adminlove520/AI-Account-Toolkit", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:eugeniughelbur/obsidian-second-brain", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "eugeniughelbur/obsidian-second-brain", "date": "2026-06-03", "createdAt": "2026-03-24", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Cross-CLI skill for Obsidian: turn your vault into a living AI-first second brain across Claude Code, Codex, Gemini, and OpenCode. 43 commands - now with /obsidian-architect to document your codebase, key-less web research, Google Calendar, and self-rewriti...", "popularity": {"value": 2096, "label": "stars"}, "url": "https://github.com/eugeniughelbur/obsidian-second-brain", "tags": ["agents", "ai-agent"]}
{"id": "github:alvinreal/awesome-opensource-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alvinreal/awesome-opensource-ai", "date": "2026-05-29", "createdAt": "2026-03-24", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Curated list of the best truly open-source AI projects, models, tools, and infrastructure.", "popularity": {"value": 3736, "label": "stars"}, "url": "https://github.com/alvinreal/awesome-opensource-ai", "tags": ["developer-tools", "generative-ai"]}
{"id": "hf-dataset:mvp-lab/LLaVA-OneVision-2-Data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mvp-lab/LLaVA-OneVision-2-Data", "date": "2026-05-11", "createdAt": "2026-03-24", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 232849 downloads.", "popularity": {"value": 232849, "label": "downloads"}, "url": "https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-2-Data", "tags": ["datasets", "format:optimized-parquet", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:introvoyz041/uspto-mol", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "introvoyz041/uspto-mol", "date": "2026-03-24", "createdAt": "2026-03-24", "sourceUpdatedAt": "2026-03-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81383 downloads.", "popularity": {"value": 81383, "label": "downloads"}, "url": "https://huggingface.co/datasets/introvoyz041/uspto-mol", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:schwein69/hagrid-subset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "schwein69/hagrid-subset", "date": "2026-03-24", "createdAt": "2026-03-24", "sourceUpdatedAt": "2026-03-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62400 downloads.", "popularity": {"value": 62400, "label": "downloads"}, "url": "https://huggingface.co/datasets/schwein69/hagrid-subset", "tags": ["computer-vision", "datasets", "gesture-recognition", "hand-gestures", "license:mit", "region:us", "size_categories:10k<n<100k", "task_categories:image-classification"]}
{"id": "hf-dataset:leibnitz-lab/colinear_scaling_models", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "leibnitz-lab/colinear_scaling_models", "date": "2026-04-29", "createdAt": "2026-03-23", "sourceUpdatedAt": "2026-04-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 102950 downloads.", "popularity": {"value": 102950, "label": "downloads"}, "url": "https://huggingface.co/datasets/leibnitz-lab/colinear_scaling_models", "tags": ["datasets", "license:gpl-2.0", "region:us"]}
{"id": "github:holaboss-ai/holaos", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "holaboss-ai/holaOS", "date": "2026-06-02", "createdAt": "2026-03-22", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Your super agent for work: local-first, learn your working context in mins and never forget it.", "popularity": {"value": 5513, "label": "stars"}, "url": "https://github.com/holaboss-ai/holaOS", "tags": ["agents", "ai-agent"]}
{"id": "github:openilink/openilink-hub", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "openilink/openilink-hub", "date": "2026-05-30", "createdAt": "2026-03-22", "sourceUpdatedAt": "2026-05-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "开源微信 Bot 管理平台 + App 应用市场 | Self-hosted WeChat Bot Platform with App Marketplace | Lark · Slack · Discord · DingTalk · GitHub · Notion · 20+ Apps | AI Tools | 7 Language SDKs", "popularity": {"value": 1315, "label": "stars"}, "url": "https://github.com/openilink/openilink-hub", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:robbyant/mdm_depth", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "robbyant/mdm_depth", "date": "2026-04-17", "createdAt": "2026-03-21", "sourceUpdatedAt": "2026-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81309 downloads.", "popularity": {"value": 81309, "label": "downloads"}, "url": "https://huggingface.co/datasets/robbyant/mdm_depth", "tags": ["3d", "arxiv:2601.17895", "datasets", "depth", "language:en", "license:apache-2.0", "modality:3d", "region:us"]}
{"id": "hf-dataset:ksolovev/FineNews", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ksolovev/FineNews", "date": "2026-03-23", "createdAt": "2026-03-21", "sourceUpdatedAt": "2026-03-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1773720 downloads.", "popularity": {"value": 1773720, "label": "downloads"}, "url": "https://huggingface.co/datasets/ksolovev/FineNews", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:joshmiao/gfmc_hyworld1.5_processed_160frames_20fps", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "joshmiao/gfmc_hyworld1.5_processed_160frames_20fps", "date": "2026-03-21", "createdAt": "2026-03-21", "sourceUpdatedAt": "2026-03-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54057 downloads.", "popularity": {"value": 54057, "label": "downloads"}, "url": "https://huggingface.co/datasets/joshmiao/gfmc_hyworld1.5_processed_160frames_20fps", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:alvinreal/awesome-autoresearch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alvinreal/awesome-autoresearch", "date": "2026-05-28", "createdAt": "2026-03-20", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Karpathy's autoresearch.", "popularity": {"value": 2146, "label": "stars"}, "url": "https://github.com/alvinreal/awesome-autoresearch", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:Sakano22/dg-storage", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Sakano22/dg-storage", "date": "2026-04-11", "createdAt": "2026-03-20", "sourceUpdatedAt": "2026-04-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53964 downloads.", "popularity": {"value": 53964, "label": "downloads"}, "url": "https://huggingface.co/datasets/Sakano22/dg-storage", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:Nithish2410/benchmark-bcplus", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Nithish2410/benchmark-bcplus", "date": "2026-03-20", "createdAt": "2026-03-20", "sourceUpdatedAt": "2026-03-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59704 downloads.", "popularity": {"value": 59704, "label": "downloads"}, "url": "https://huggingface.co/datasets/Nithish2410/benchmark-bcplus", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:Kllove/SwissCube", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Kllove/SwissCube", "date": "2026-03-19", "createdAt": "2026-03-19", "sourceUpdatedAt": "2026-03-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52544 downloads.", "popularity": {"value": 52544, "label": "downloads"}, "url": "https://huggingface.co/datasets/Kllove/SwissCube", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:lxf746/any-auto-register", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lxf746/any-auto-register", "date": "2026-06-04", "createdAt": "2026-03-18", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Auto-register & manage accounts for ChatGPT, Cursor, Kiro, Grok, Windsurf, Trae & 13+ AI platforms · Protocol/browser dual-mode · Plugin-based · One-click Mac/Windows desktop app", "popularity": {"value": 2631, "label": "stars"}, "url": "https://github.com/lxf746/any-auto-register", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:rohitg00/ai-engineering-from-scratch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "rohitg00/ai-engineering-from-scratch", "date": "2026-06-03", "createdAt": "2026-03-18", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Learn it. Build it. Ship it for others.", "popularity": {"value": 27948, "label": "stars"}, "url": "https://github.com/rohitg00/ai-engineering-from-scratch", "tags": ["llm", "tools"]}
{"id": "github:lightningpixel/modly", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lightningpixel/modly", "date": "2026-06-02", "createdAt": "2026-03-17", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Desktop app to generate 3D models from images using local AI — runs entirely on your GPU", "popularity": {"value": 3839, "label": "stars"}, "url": "https://github.com/lightningpixel/modly", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:introvoyz041/PhysicalAI-Robotics-Open-H-Embodiment", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "introvoyz041/PhysicalAI-Robotics-Open-H-Embodiment", "date": "2026-03-16", "createdAt": "2026-03-16", "sourceUpdatedAt": "2026-03-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56307 downloads.", "popularity": {"value": 56307, "label": "downloads"}, "url": "https://huggingface.co/datasets/introvoyz041/PhysicalAI-Robotics-Open-H-Embodiment", "tags": ["datasets", "healthcare", "license:cc-by-4.0", "region:us", "robotics"]}
{"id": "hf-dataset:ccoffee20/flatpak", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ccoffee20/flatpak", "date": "2026-04-10", "createdAt": "2026-03-15", "sourceUpdatedAt": "2026-04-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 179543 downloads.", "popularity": {"value": 179543, "label": "downloads"}, "url": "https://huggingface.co/datasets/ccoffee20/flatpak", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:kantor3/CADS-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "kantor3/CADS-dataset", "date": "2026-03-15", "createdAt": "2026-03-15", "sourceUpdatedAt": "2026-03-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 83025 downloads.", "popularity": {"value": 83025, "label": "downloads"}, "url": "https://huggingface.co/datasets/kantor3/CADS-dataset", "tags": ["3d", "anatomy", "arxiv:2507.22953", "ct", "datasets", "format:csv", "image", "library:datasets"]}
{"id": "github:jackwener/opencli", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jackwener/OpenCLI", "date": "2026-06-02", "createdAt": "2026-03-14", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Make Any Website into CLI & Use your logged-in browser by AI agent.", "popularity": {"value": 23435, "label": "stars"}, "url": "https://github.com/jackwener/OpenCLI", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:AplusX/EgoPoseVR", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AplusX/EgoPoseVR", "date": "2026-04-12", "createdAt": "2026-03-14", "sourceUpdatedAt": "2026-04-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56886 downloads.", "popularity": {"value": 56886, "label": "downloads"}, "url": "https://huggingface.co/datasets/AplusX/EgoPoseVR", "tags": ["arxiv:2602.05590", "datasets", "egocentric", "license:cc-by-4.0", "motion-capture", "pose-estimation", "region:us", "rgbd"]}
{"id": "github:xalgord/xalgorix", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "xalgord/xalgorix", "date": "2026-06-03", "createdAt": "2026-03-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Xalgorix - The Most Powerful Open-Source AI Pentesting Agent", "popularity": {"value": 572, "label": "stars"}, "url": "https://github.com/xalgord/xalgorix", "tags": ["agents", "ai-tools"]}
{"id": "github:jcodesmore/ai-website-cloner-template", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "JCodesMore/ai-website-cloner-template", "date": "2026-06-01", "createdAt": "2026-03-13", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Clone any website with one command using AI coding agents", "popularity": {"value": 16182, "label": "stars"}, "url": "https://github.com/JCodesMore/ai-website-cloner-template", "tags": ["agents", "ai-tools"]}
{"id": "github:narcooo/inkos", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Narcooo/inkos", "date": "2026-06-03", "createdAt": "2026-03-12", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Autonomous novel writing AI Agent — agents write, audit, and revise novels with human review gates", "popularity": {"value": 6872, "label": "stars"}, "url": "https://github.com/Narcooo/inkos", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:MrigLabIITRopar/GroMo25", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "MrigLabIITRopar/GroMo25", "date": "2026-04-02", "createdAt": "2026-03-12", "sourceUpdatedAt": "2026-04-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 68843 downloads.", "popularity": {"value": 68843, "label": "downloads"}, "url": "https://huggingface.co/datasets/MrigLabIITRopar/GroMo25", "tags": ["age-estimation", "agriculture", "datasets", "format:csv", "language:en", "leaf-counting", "library:dask", "library:datasets"]}
{"id": "hf-dataset:liguang0115/EgoEdit", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "liguang0115/EgoEdit", "date": "2026-03-18", "createdAt": "2026-03-12", "sourceUpdatedAt": "2026-03-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 88320 downloads.", "popularity": {"value": 88320, "label": "downloads"}, "url": "https://huggingface.co/datasets/liguang0115/EgoEdit", "tags": ["arxiv:2512.06065", "datasets", "editing", "language:en", "modality:video", "region:us", "size_categories:10k<n<100k", "video"]}
{"id": "github:czl9707/build-your-own-openclaw", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "czl9707/build-your-own-openclaw", "date": "2026-06-01", "createdAt": "2026-03-11", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "A step-by-step guide to build your own AI agent.", "popularity": {"value": 1687, "label": "stars"}, "url": "https://github.com/czl9707/build-your-own-openclaw", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:ropedia-ai/xperience-10m", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ropedia-ai/xperience-10m", "date": "2026-04-21", "createdAt": "2026-03-11", "sourceUpdatedAt": "2026-04-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 112713 downloads.", "popularity": {"value": 112713, "label": "downloads"}, "url": "https://huggingface.co/datasets/ropedia-ai/xperience-10m", "tags": ["3d", "4d", "audio", "captions", "datasets", "depth", "egocentric", "embodied-ai"]}
{"id": "hf-model:google/gemma-4-26B-A4B-it", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "google/gemma-4-26B-A4B-it", "date": "2026-03-11", "createdAt": "2026-03-11", "sourceUpdatedAt": "2026-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 11696495 downloads and tags: transformers, safetensors, gemma4, image-text-to-text.", "popularity": {"value": 11696495, "label": "downloads"}, "url": "https://huggingface.co/google/gemma-4-26B-A4B-it", "tags": ["base_model:finetune:google/gemma-4-26b-a4b", "base_model:google/gemma-4-26b-a4b", "conversational", "gemma4", "image-text-to-text", "license:apache-2.0", "llm", "safetensors"]}
{"id": "hf-model:google/gemma-4-31B-it", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "google/gemma-4-31B-it", "date": "2026-03-11", "createdAt": "2026-03-11", "sourceUpdatedAt": "2026-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 11271936 downloads and tags: transformers, safetensors, gemma4, image-text-to-text.", "popularity": {"value": 11271936, "label": "downloads"}, "url": "https://huggingface.co/google/gemma-4-31B-it", "tags": ["base_model:finetune:google/gemma-4-31b", "base_model:google/gemma-4-31b", "conversational", "gemma4", "image-text-to-text", "license:apache-2.0", "llm", "safetensors"]}
{"id": "github:wanshuiyin/auto-claude-code-research-in-sleep", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "wanshuiyin/Auto-claude-code-research-in-sleep", "date": "2026-06-02", "createdAt": "2026-03-10", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.", "popularity": {"value": 11331, "label": "stars"}, "url": "https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:Maximilians/ps2_hf1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Maximilians/ps2_hf1", "date": "2026-04-10", "createdAt": "2026-03-10", "sourceUpdatedAt": "2026-04-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 572234 downloads.", "popularity": {"value": 572234, "label": "downloads"}, "url": "https://huggingface.co/datasets/Maximilians/ps2_hf1", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:HennyPr/ps2_hf2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HennyPr/ps2_hf2", "date": "2026-04-05", "createdAt": "2026-03-10", "sourceUpdatedAt": "2026-04-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 779914 downloads.", "popularity": {"value": 779914, "label": "downloads"}, "url": "https://huggingface.co/datasets/HennyPr/ps2_hf2", "tags": ["datasets", "format:text", "library:datasets", "library:mlcroissant", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:lhmd/re10k_torch", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lhmd/re10k_torch", "date": "2026-05-26", "createdAt": "2026-03-09", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58538 downloads.", "popularity": {"value": 58538, "label": "downloads"}, "url": "https://huggingface.co/datasets/lhmd/re10k_torch", "tags": ["arxiv:1805.09817", "arxiv:2505.23734", "arxiv:2509.19297", "arxiv:2605.26115", "datasets", "license:mit", "region:us", "task_categories:image-to-3d"]}
{"id": "github:bergside/awesome-design-skills", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bergside/awesome-design-skills", "date": "2026-05-25", "createdAt": "2026-03-09", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "List of 67 awesome DESIGN.md and SKILL.md design skill files for agentic tools like Claude Design, Google Stitch, Codex, Cursor, and other AI tools", "popularity": {"value": 1107, "label": "stars"}, "url": "https://github.com/bergside/awesome-design-skills", "tags": ["agents", "ai-tools"]}
{"id": "github:aiming-lab/metaclaw", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "aiming-lab/MetaClaw", "date": "2026-05-23", "createdAt": "2026-03-09", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🦞 Just talk to your agent — it learns and EVOLVES 🧬.", "popularity": {"value": 3424, "label": "stars"}, "url": "https://github.com/aiming-lab/MetaClaw", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:Xbox186/LARD_V2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Xbox186/LARD_V2", "date": "2026-03-09", "createdAt": "2026-03-09", "sourceUpdatedAt": "2026-03-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70684 downloads.", "popularity": {"value": 70684, "label": "downloads"}, "url": "https://huggingface.co/datasets/Xbox186/LARD_V2", "tags": ["aircraft", "datasets", "landing", "license:mit", "modality:image", "region:us", "runway", "sim2real"]}
{"id": "hf-dataset:xlangai/osworld_v2_file_cache", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "xlangai/osworld_v2_file_cache", "date": "2026-05-24", "createdAt": "2026-03-07", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46893 downloads.", "popularity": {"value": 46893, "label": "downloads"}, "url": "https://huggingface.co/datasets/xlangai/osworld_v2_file_cache", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:balatubs123/kumagong", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "balatubs123/kumagong", "date": "2026-03-07", "createdAt": "2026-03-07", "sourceUpdatedAt": "2026-03-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 65571 downloads.", "popularity": {"value": 65571, "label": "downloads"}, "url": "https://huggingface.co/datasets/balatubs123/kumagong", "tags": ["datasets", "lerobot", "license:cc-by-nc-sa-4.0", "region:us", "task_categories:robotics"]}
{"id": "hf-dataset:Tranxxx/Charvastamy", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Tranxxx/Charvastamy", "date": "2026-03-06", "createdAt": "2026-03-06", "sourceUpdatedAt": "2026-03-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56518 downloads.", "popularity": {"value": 56518, "label": "downloads"}, "url": "https://huggingface.co/datasets/Tranxxx/Charvastamy", "tags": ["arxiv:2602.10116", "datasets", "embodied-ai", "interactive-scenes", "language:en", "license:apache-2.0", "region:us", "robotics"]}
{"id": "github:jjang-ai/mlxstudio", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jjang-ai/mlxstudio", "date": "2026-06-02", "createdAt": "2026-03-05", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "MLX Studio - Home of JANG_Q - Image Gen/Edit + Chat/Code All in one - + OpenClaw (Anthropic API)", "popularity": {"value": 765, "label": "stars"}, "url": "https://github.com/jjang-ai/mlxstudio", "tags": ["inference"]}
{"id": "github:andyyyy64/whichllm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Andyyyy64/whichllm", "date": "2026-06-04", "createdAt": "2026-03-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.", "popularity": {"value": 2672, "label": "stars"}, "url": "https://github.com/Andyyyy64/whichllm", "tags": ["inference"]}
{"id": "hf-dataset:RosettaCommons/ProteinMPNN", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "RosettaCommons/ProteinMPNN", "date": "2026-04-24", "createdAt": "2026-03-04", "sourceUpdatedAt": "2026-04-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48176 downloads.", "popularity": {"value": 48176, "label": "downloads"}, "url": "https://huggingface.co/datasets/RosettaCommons/ProteinMPNN", "tags": ["biology", "chemistry", "datasets", "language:en", "license:other", "region:us"]}
{"id": "github:bergside/typeui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bergside/typeui", "date": "2026-06-03", "createdAt": "2026-03-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build better UI with Codex, Claude, Cursor and other AI tools", "popularity": {"value": 1039, "label": "stars"}, "url": "https://github.com/bergside/typeui", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:AnonymCode/trash", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AnonymCode/trash", "date": "2026-03-31", "createdAt": "2026-03-03", "sourceUpdatedAt": "2026-03-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 65786 downloads.", "popularity": {"value": 65786, "label": "downloads"}, "url": "https://huggingface.co/datasets/AnonymCode/trash", "tags": ["datasets", "modality:image", "region:us"]}
{"id": "hf-dataset:deepguess/wrf-250m-severe-weather", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "deepguess/wrf-250m-severe-weather", "date": "2026-03-04", "createdAt": "2026-03-03", "sourceUpdatedAt": "2026-03-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52025 downloads.", "popularity": {"value": 52025, "label": "downloads"}, "url": "https://huggingface.co/datasets/deepguess/wrf-250m-severe-weather", "tags": ["atmospheric-science", "datasets", "format:json", "high-resolution", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:karpathy/climbmix-400b-shuffle", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "karpathy/climbmix-400b-shuffle", "date": "2026-03-03", "createdAt": "2026-03-03", "sourceUpdatedAt": "2026-03-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73739 downloads.", "popularity": {"value": 73739, "label": "downloads"}, "url": "https://huggingface.co/datasets/karpathy/climbmix-400b-shuffle", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:mit", "modality:text"]}
{"id": "hf-dataset:Hollow12334/fsc-180k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Hollow12334/fsc-180k", "date": "2026-03-03", "createdAt": "2026-03-03", "sourceUpdatedAt": "2026-03-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62414 downloads.", "popularity": {"value": 62414, "label": "downloads"}, "url": "https://huggingface.co/datasets/Hollow12334/fsc-180k", "tags": ["datasets", "region:us"]}
{"id": "github:comet-ml/opik-openclaw", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "comet-ml/opik-openclaw", "date": "2026-06-02", "createdAt": "2026-03-02", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🦞 Official plugin for OpenClaw that exports agent traces to Opik. See and monitor agent behaviour, cost, tokens, errors and more.", "popularity": {"value": 617, "label": "stars"}, "url": "https://github.com/comet-ml/opik-openclaw", "tags": ["agents", "evaluation"]}
{"id": "github:googleworkspace/cli", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "googleworkspace/cli", "date": "2026-06-01", "createdAt": "2026-03-02", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Google Workspace CLI — one command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Dynamically built from Google Discovery Service. Includes AI agent skills.", "popularity": {"value": 26824, "label": "stars"}, "url": "https://github.com/googleworkspace/cli", "tags": ["agents", "ai-agent"]}
{"id": "github:leoyeai/openclaw-master-skills", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "LeoYeAI/openclaw-master-skills", "date": "2026-06-01", "createdAt": "2026-03-02", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai", "popularity": {"value": 2011, "label": "stars"}, "url": "https://github.com/LeoYeAI/openclaw-master-skills", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:OpenDataArena/OpenDataArena-scored-data-2603", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "OpenDataArena/OpenDataArena-scored-data-2603", "date": "2026-05-28", "createdAt": "2026-03-02", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60659 downloads.", "popularity": {"value": 60659, "label": "downloads"}, "url": "https://huggingface.co/datasets/OpenDataArena/OpenDataArena-scored-data-2603", "tags": ["arxiv:2308.05696", "arxiv:2308.07074", "arxiv:2312.15685", "arxiv:2402.09739", "arxiv:2503.00808", "arxiv:2503.11441", "arxiv:2507.01352", "arxiv:2512.14051"]}
{"id": "hf-dataset:genarenadata/backup-leaderboard-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "genarenadata/backup-leaderboard-data", "date": "2026-03-02", "createdAt": "2026-03-02", "sourceUpdatedAt": "2026-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63434 downloads.", "popularity": {"value": 63434, "label": "downloads"}, "url": "https://huggingface.co/datasets/genarenadata/backup-leaderboard-data", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:Emmyc2/psp", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Emmyc2/psp", "date": "2026-03-06", "createdAt": "2026-03-01", "sourceUpdatedAt": "2026-03-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 493271 downloads.", "popularity": {"value": 493271, "label": "downloads"}, "url": "https://huggingface.co/datasets/Emmyc2/psp", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:siril-spcc/gaia", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "siril-spcc/gaia", "date": "2026-03-02", "createdAt": "2026-03-01", "sourceUpdatedAt": "2026-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 313336 downloads.", "popularity": {"value": 313336, "label": "downloads"}, "url": "https://huggingface.co/datasets/siril-spcc/gaia", "tags": ["datasets", "license:gpl-3.0", "region:us"]}
{"id": "github:vasu-devs/justhireme", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vasu-devs/JustHireMe", "date": "2026-06-04", "createdAt": "2026-02-28", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Local-first AI job intelligence workbench for scraping roles, ranking fit, and generating tailored application materials.", "popularity": {"value": 1948, "label": "stars"}, "url": "https://github.com/vasu-devs/JustHireMe", "tags": ["tools", "vector-database"]}
{"id": "github:agentsmesh/agentsmesh", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AgentsMesh/AgentsMesh", "date": "2026-06-03", "createdAt": "2026-02-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The AI Agent Workforce Platform — where teams scale beyond headcount. Give every team member an AI agent squad.", "popularity": {"value": 2185, "label": "stars"}, "url": "https://github.com/AgentsMesh/AgentsMesh", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:tienmanh93/MDC", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tienmanh93/MDC", "date": "2026-05-23", "createdAt": "2026-02-28", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 109973 downloads.", "popularity": {"value": 109973, "label": "downloads"}, "url": "https://huggingface.co/datasets/tienmanh93/MDC", "tags": ["datasets", "format:audiofolder", "library:datasets", "library:mlcroissant", "modality:audio", "region:us", "size_categories:n<1k"]}
{"id": "hf-model:Qwen/Qwen3.5-4B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3.5-4B", "date": "2026-02-27", "createdAt": "2026-02-27", "sourceUpdatedAt": "2026-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 10126486 downloads and tags: transformers, safetensors, qwen3_5, image-text-to-text.", "popularity": {"value": 10126486, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3.5-4B", "tags": ["base_model:finetune:qwen/qwen3.5-4b-base", "base_model:qwen/qwen3.5-4b-base", "conversational", "image-text-to-text", "license:apache-2.0", "llm", "qwen3_5", "safetensors"]}
{"id": "github:qingchencloud/clawpanel", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "qingchencloud/clawpanel", "date": "2026-06-01", "createdAt": "2026-02-26", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🦞 OpenClaw & Hermes Agent 多引擎 AI 管理面板 — 内置 AI 助手（工具调用 + 图片识别 + 多模态），一键安装 | Tauri v2 跨平台桌面应用 | 11 种语言", "popularity": {"value": 2809, "label": "stars"}, "url": "https://github.com/qingchencloud/clawpanel", "tags": ["agents", "ai-agent"]}
{"id": "github:giancarloerra/socraticode", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "giancarloerra/SocratiCode", "date": "2026-05-27", "createdAt": "2026-02-26", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware...", "popularity": {"value": 2792, "label": "stars"}, "url": "https://github.com/giancarloerra/SocratiCode", "tags": ["tools", "vector-database"]}
{"id": "hf-dataset:haofeixu/dl3dv-960p-chunks", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "haofeixu/dl3dv-960p-chunks", "date": "2026-02-27", "createdAt": "2026-02-26", "sourceUpdatedAt": "2026-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71409 downloads.", "popularity": {"value": 71409, "label": "downloads"}, "url": "https://huggingface.co/datasets/haofeixu/dl3dv-960p-chunks", "tags": ["datasets", "license:other", "region:us"]}
{"id": "github:raullenchai/rapid-mlx", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "raullenchai/Rapid-MLX", "date": "2026-06-04", "createdAt": "2026-02-25", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing. Drop-in OpenAI replacement. Works with Claude Code, Cursor, Aider.", "popularity": {"value": 2658, "label": "stars"}, "url": "https://github.com/raullenchai/Rapid-MLX", "tags": ["inference"]}
{"id": "github:nexu-io/nexu", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nexu-io/nexu", "date": "2026-04-26", "createdAt": "2026-02-25", "sourceUpdatedAt": "2026-04-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The simplest desktop client for OpenClaw 🦞 — bridge your Agent to WeChat, Feishu, Slack & Discord in one click. Works with Claude Code, Codex & any LLM. BYOK, Oauth, local-first, chat from your phone 24/7.", "popularity": {"value": 3083, "label": "stars"}, "url": "https://github.com/nexu-io/nexu", "tags": ["agents", "ai-agent"]}
{"id": "github:panniantong/agent-reach", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Panniantong/Agent-Reach", "date": "2026-05-18", "createdAt": "2026-02-24", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.", "popularity": {"value": 21019, "label": "stars"}, "url": "https://github.com/Panniantong/Agent-Reach", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:Forithmus/MR-RATE", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Forithmus/MR-RATE", "date": "2026-04-23", "createdAt": "2026-02-24", "sourceUpdatedAt": "2026-04-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 97066 downloads.", "popularity": {"value": 97066, "label": "downloads"}, "url": "https://huggingface.co/datasets/Forithmus/MR-RATE", "tags": ["3d-medical-imaging", "brain-mri", "computer-vision", "datasets", "diagnostic-imaging", "foundation-model", "healthcare", "huggingscience"]}
{"id": "github:alexanys/awesome-openclaw-usecases-zh", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AlexAnys/awesome-openclaw-usecases-zh", "date": "2026-06-03", "createdAt": "2026-02-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🇨🇳 OpenClaw中文用例大全 | 50个真实场景 | 国内特色 + 海外案例的国内适配 | 自动化办公·内容创作·运维·AI助理·知识管理 | 新手友好", "popularity": {"value": 4281, "label": "stars"}, "url": "https://github.com/AlexAnys/awesome-openclaw-usecases-zh", "tags": ["agents", "ai-agent"]}
{"id": "github:unohee/openswarm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "unohee/OpenSwarm", "date": "2026-06-03", "createdAt": "2026-02-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenSwarm — Autonomous AI dev team orchestrator powered by Claude Code CLI. Discord control, Linear integration, cognitive memory.", "popularity": {"value": 799, "label": "stars"}, "url": "https://github.com/unohee/OpenSwarm", "tags": ["developer-tools", "vector-database"]}
{"id": "hf-dataset:blsmash044/SA-Med3D-140K", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "blsmash044/SA-Med3D-140K", "date": "2026-02-23", "createdAt": "2026-02-23", "sourceUpdatedAt": "2026-02-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73015 downloads.", "popularity": {"value": 73015, "label": "downloads"}, "url": "https://huggingface.co/datasets/blsmash044/SA-Med3D-140K", "tags": ["arxiv:2310.15161", "datasets", "license:apache-2.0", "region:us"]}
{"id": "github:nextlevelbuilder/goclaw", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nextlevelbuilder/goclaw", "date": "2026-06-03", "createdAt": "2026-02-22", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety.", "popularity": {"value": 3220, "label": "stars"}, "url": "https://github.com/nextlevelbuilder/goclaw", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:Publicus/common_crawl_meta_indexes", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Publicus/common_crawl_meta_indexes", "date": "2026-02-27", "createdAt": "2026-02-22", "sourceUpdatedAt": "2026-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 84416 downloads.", "popularity": {"value": 84416, "label": "downloads"}, "url": "https://huggingface.co/datasets/Publicus/common_crawl_meta_indexes", "tags": ["datasets", "modality:tabular", "modality:text", "region:us", "size_categories:1b<n<10b"]}
{"id": "hf-dataset:Publicus/common_crawl_pointers_by_collection", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Publicus/common_crawl_pointers_by_collection", "date": "2026-02-26", "createdAt": "2026-02-22", "sourceUpdatedAt": "2026-02-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 92942 downloads.", "popularity": {"value": 92942, "label": "downloads"}, "url": "https://huggingface.co/datasets/Publicus/common_crawl_pointers_by_collection", "tags": ["datasets", "region:us"]}
{"id": "github:777genius/agent-teams-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "777genius/agent-teams-ai", "date": "2026-06-03", "createdAt": "2026-02-21", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "You're the boss, agents are your team. They handle tasks on their own, message each other, and review each other's work. You just watch the kanban board and give high-level commands. Codex/Claude/OpenCode(200+ models, 75+ LLM providers, free models no auth)...", "popularity": {"value": 1042, "label": "stars"}, "url": "https://github.com/777genius/agent-teams-ai", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:zlab-princeton/Vero-600k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "zlab-princeton/Vero-600k", "date": "2026-04-13", "createdAt": "2026-02-21", "sourceUpdatedAt": "2026-04-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67721 downloads.", "popularity": {"value": 67721, "label": "downloads"}, "url": "https://huggingface.co/datasets/zlab-princeton/Vero-600k", "tags": ["arxiv:2604.04917", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:laion/Scientific-Summaries", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "laion/Scientific-Summaries", "date": "2026-05-21", "createdAt": "2026-02-19", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63889 downloads.", "popularity": {"value": 63889, "label": "downloads"}, "url": "https://huggingface.co/datasets/laion/Scientific-Summaries", "tags": ["annotations_creators:machine-generated", "arxiv", "arxiv:2502.19413", "bm25", "datasets", "faiss", "format:parquet", "language:en"]}
{"id": "github:rightnow-ai/picolm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "RightNow-AI/picolm", "date": "2026-02-22", "createdAt": "2026-02-19", "sourceUpdatedAt": "2026-02-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Run a 1-billion parameter LLM on a $10 board with 256MB RAM", "popularity": {"value": 1641, "label": "stars"}, "url": "https://github.com/RightNow-AI/picolm", "tags": ["inference"]}
{"id": "github:johannesjo/parallel-code", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "johannesjo/parallel-code", "date": "2026-06-03", "createdAt": "2026-02-18", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Run Claude Code, Codex, and Gemini side by side — each in      its own git worktree", "popularity": {"value": 700, "label": "stars"}, "url": "https://github.com/johannesjo/parallel-code", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:rozumov/TurkmenSpeech", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rozumov/TurkmenSpeech", "date": "2026-02-18", "createdAt": "2026-02-18", "sourceUpdatedAt": "2026-02-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 65414 downloads.", "popularity": {"value": 65414, "label": "downloads"}, "url": "https://huggingface.co/datasets/rozumov/TurkmenSpeech", "tags": ["datasets", "language:tk", "license:cc-by-nc-4.0", "region:us", "size_categories:100k<n<1m", "task_categories:automatic-speech-recognition", "task_categories:text-to-speech"]}
{"id": "hf-dataset:wisent-ai/activations", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "wisent-ai/activations", "date": "2026-06-03", "createdAt": "2026-02-17", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54870 downloads.", "popularity": {"value": 54870, "label": "downloads"}, "url": "https://huggingface.co/datasets/wisent-ai/activations", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:robbyant/robotwin-clean-and-aug-lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "robbyant/robotwin-clean-and-aug-lerobot", "date": "2026-02-17", "createdAt": "2026-02-17", "sourceUpdatedAt": "2026-02-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 104268 downloads.", "popularity": {"value": 104268, "label": "downloads"}, "url": "https://huggingface.co/datasets/robbyant/robotwin-clean-and-aug-lerobot", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:10k<n<100k"]}
{"id": "hf-dataset:niklastr/many-oligos", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "niklastr/many-oligos", "date": "2026-03-11", "createdAt": "2026-02-16", "sourceUpdatedAt": "2026-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 99900 downloads.", "popularity": {"value": 99900, "label": "downloads"}, "url": "https://huggingface.co/datasets/niklastr/many-oligos", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:samfatnassi/gaia-dr3", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "samfatnassi/gaia-dr3", "date": "2026-02-21", "createdAt": "2026-02-16", "sourceUpdatedAt": "2026-02-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53584 downloads.", "popularity": {"value": 53584, "label": "downloads"}, "url": "https://huggingface.co/datasets/samfatnassi/gaia-dr3", "tags": ["astronomy", "astrophysics", "datasets", "gaia-dr3", "license:apache-2.0", "modality:tabular", "region:us", "size_categories:100m<n<1b"]}
{"id": "hf-dataset:bezzam/coraal", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bezzam/coraal", "date": "2026-02-16", "createdAt": "2026-02-16", "sourceUpdatedAt": "2026-02-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 87333 downloads.", "popularity": {"value": 87333, "label": "downloads"}, "url": "https://huggingface.co/datasets/bezzam/coraal", "tags": ["datasets", "format:optimized-parquet", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "github:liaohch3/claude-tap", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "liaohch3/claude-tap", "date": "2026-06-04", "createdAt": "2026-02-15", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Intercept and inspect Coding Agent API traffic from Claude Code, Codex CLI, Gemini CLI, Cursor CLI, OpenCode, Kimi, Pi, and Hermes in a local trace viewer.", "popularity": {"value": 1347, "label": "stars"}, "url": "https://github.com/liaohch3/claude-tap", "tags": ["agents", "ai-tools"]}
{"id": "github:alexsjones/llmfit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AlexsJones/llmfit", "date": "2026-06-03", "createdAt": "2026-02-15", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hundreds of models & providers. One command to find what runs on your hardware.", "popularity": {"value": 27318, "label": "stars"}, "url": "https://github.com/AlexsJones/llmfit", "tags": ["llm", "tools"]}
{"id": "hf-dataset:HuggingFaceFW/finephrase", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/finephrase", "date": "2026-03-31", "createdAt": "2026-02-15", "sourceUpdatedAt": "2026-03-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 457425 downloads.", "popularity": {"value": 457425, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/finephrase", "tags": ["annotations_creators:machine-generated", "datasets", "datatrove", "fineweb-edu", "language:en", "language_creators:found", "license:odc-by", "modality:tabular"]}
{"id": "hf-dataset:endomorphosis/common_crawl_meta_indexes", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "endomorphosis/common_crawl_meta_indexes", "date": "2026-02-22", "createdAt": "2026-02-15", "sourceUpdatedAt": "2026-02-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 213222 downloads.", "popularity": {"value": 213222, "label": "downloads"}, "url": "https://huggingface.co/datasets/endomorphosis/common_crawl_meta_indexes", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:GEAR-Dreams/DreamZero-DROID-Data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "GEAR-Dreams/DreamZero-DROID-Data", "date": "2026-02-17", "createdAt": "2026-02-15", "sourceUpdatedAt": "2026-02-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 194279 downloads.", "popularity": {"value": 194279, "label": "downloads"}, "url": "https://huggingface.co/datasets/GEAR-Dreams/DreamZero-DROID-Data", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:video", "region:us", "size_categories:1k<n<10k"]}
{"id": "hf-dataset:gfdg34fsd/rdp", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gfdg34fsd/rdp", "date": "2026-05-12", "createdAt": "2026-02-14", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46741 downloads.", "popularity": {"value": 46741, "label": "downloads"}, "url": "https://huggingface.co/datasets/gfdg34fsd/rdp", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:qimma/leaderboard-details", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "qimma/leaderboard-details", "date": "2026-05-20", "createdAt": "2026-02-13", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67918 downloads.", "popularity": {"value": 67918, "label": "downloads"}, "url": "https://huggingface.co/datasets/qimma/leaderboard-details", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:evaleval/EEE_datastore", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "evaleval/EEE_datastore", "date": "2026-06-03", "createdAt": "2026-02-11", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81569 downloads.", "popularity": {"value": 81569, "label": "downloads"}, "url": "https://huggingface.co/datasets/evaleval/EEE_datastore", "tags": ["datasets", "license:mit", "modality:text", "region:us", "size_categories:10k<n<100k"]}
{"id": "github:kimyx0207/ai-coding-guide-zh", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "KimYx0207/AI-Coding-Guide-Zh", "date": "2026-06-03", "createdAt": "2026-02-11", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Claude Code + OpenClaw + Codex 中文教程 | 39篇完整教程 + 1张速查卡 | 80万+内容量 | 1500+实操示例 | AI Coding / Agent 三线学习路径", "popularity": {"value": 4354, "label": "stars"}, "url": "https://github.com/KimYx0207/AI-Coding-Guide-Zh", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:GildasLeDrogoff/spotify-huge-track-analysis-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "GildasLeDrogoff/spotify-huge-track-analysis-dataset", "date": "2026-02-11", "createdAt": "2026-02-11", "sourceUpdatedAt": "2026-02-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60984 downloads.", "popularity": {"value": 60984, "label": "downloads"}, "url": "https://huggingface.co/datasets/GildasLeDrogoff/spotify-huge-track-analysis-dataset", "tags": ["audio-features", "clustering", "data-analysis", "datasets", "doi:10.57967/hf/8926", "eda", "exploratory-data-analysis", "language:en"]}
{"id": "github:open-webui/open-terminal", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "open-webui/open-terminal", "date": "2026-04-17", "createdAt": "2026-02-10", "sourceUpdatedAt": "2026-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A computer you can curl ⚡", "popularity": {"value": 2636, "label": "stars"}, "url": "https://github.com/open-webui/open-terminal", "tags": ["ai-tools", "ui-demo"]}
{"id": "hf-dataset:endomorphosis/common_crawl_pointers_by_collection", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "endomorphosis/common_crawl_pointers_by_collection", "date": "2026-02-22", "createdAt": "2026-02-10", "sourceUpdatedAt": "2026-02-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 98044 downloads.", "popularity": {"value": 98044, "label": "downloads"}, "url": "https://huggingface.co/datasets/endomorphosis/common_crawl_pointers_by_collection", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:Ahnuf/Military_Aircraft_Detection_Classification_Image_Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Ahnuf/Military_Aircraft_Detection_Classification_Image_Dataset", "date": "2026-02-11", "createdAt": "2026-02-10", "sourceUpdatedAt": "2026-02-11", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46482 downloads.", "popularity": {"value": 46482, "label": "downloads"}, "url": "https://huggingface.co/datasets/Ahnuf/Military_Aircraft_Detection_Classification_Image_Dataset", "tags": ["aerospace", "aircraft", "birds", "commercial-aircraft", "datasets", "defense", "drones", "license:apache-2.0"]}
{"id": "hf-dataset:mhaamh19/prophet-mosque-library", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mhaamh19/prophet-mosque-library", "date": "2026-02-10", "createdAt": "2026-02-10", "sourceUpdatedAt": "2026-02-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 163836 downloads.", "popularity": {"value": 163836, "label": "downloads"}, "url": "https://huggingface.co/datasets/mhaamh19/prophet-mosque-library", "tags": ["datasets", "language:ar", "license:mit", "region:us", "size_categories:10k<n<100k", "task_categories:image-to-text"]}
{"id": "hf-dataset:aadityabuilds/tree-distribution-shift", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "aadityabuilds/tree-distribution-shift", "date": "2026-03-02", "createdAt": "2026-02-09", "sourceUpdatedAt": "2026-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51491 downloads.", "popularity": {"value": 51491, "label": "downloads"}, "url": "https://huggingface.co/datasets/aadityabuilds/tree-distribution-shift", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:tabular", "modality:text"]}
{"id": "hf-dataset:arekborucki/bridge_orig_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "arekborucki/bridge_orig_lerobot", "date": "2026-02-09", "createdAt": "2026-02-09", "sourceUpdatedAt": "2026-02-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59955 downloads.", "popularity": {"value": 59955, "label": "downloads"}, "url": "https://huggingface.co/datasets/arekborucki/bridge_orig_lerobot", "tags": ["bridge_orig", "datasets", "lerobot", "license:apache-2.0", "openx", "region:us", "rlds", "task_categories:robotics"]}
{"id": "github:likeslines-maker/vectorrag.net", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "likeslines-maker/VectorRAG.Net", "date": "2026-06-03", "createdAt": "2026-02-08", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "VectorRAG.Net is a .NET-native high-performance vector database library for semantic search and RAG (Retrieval-Augmented Generation). Core search is based on Random Hyperplane LSH candidate generation with exact rerank by dot/cosine.", "popularity": {"value": 559, "label": "stars"}, "url": "https://github.com/likeslines-maker/VectorRAG.Net", "tags": ["vector-database", "vector-db"]}
{"id": "hf-dataset:Kthera/pesoz", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Kthera/pesoz", "date": "2026-04-04", "createdAt": "2026-02-08", "sourceUpdatedAt": "2026-04-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 585210 downloads.", "popularity": {"value": 585210, "label": "downloads"}, "url": "https://huggingface.co/datasets/Kthera/pesoz", "tags": ["datasets", "region:us"]}
{"id": "github:arcreel/arcreel", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ArcReel/ArcReel", "date": "2026-06-04", "createdAt": "2026-02-07", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Agent 驱动的开源视频生成工作台 — 小说→角色/场景/道具设计→剧本→分镜图→视频，跨镜头角色与场景一致 | Open-source AI video workspace powered by AI Agents, Nano Banana 2 & Veo 3.1 / Grok / Seedance / OpenAI", "popularity": {"value": 2462, "label": "stars"}, "url": "https://github.com/ArcReel/ArcReel", "tags": ["ai-agent", "video-tools"]}
{"id": "github:matt1398/claude-devtools", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "matt1398/claude-devtools", "date": "2026-05-13", "createdAt": "2026-02-07", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The missing DevTools for Claude Code — inspect session logs, tool calls, token usage, subagents, and context window in a visual UI. Free, open source.", "popularity": {"value": 3513, "label": "stars"}, "url": "https://github.com/matt1398/claude-devtools", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:nvidia/PhysicalAI-Robotics-Open-H-Embodiment", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/PhysicalAI-Robotics-Open-H-Embodiment", "date": "2026-05-25", "createdAt": "2026-02-06", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 75236 downloads.", "popularity": {"value": 75236, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-Open-H-Embodiment", "tags": ["datasets", "healthcare", "library:datasets", "library:mlcroissant", "license:cc-by-4.0", "modality:image", "modality:video", "region:us"]}
{"id": "github:llmsresearch/paperbanana", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "llmsresearch/paperbanana", "date": "2026-05-21", "createdAt": "2026-02-04", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open source implementation and extension of Google Research’s PaperBanana for automated academic figures, diagrams, and research visuals, expanded to new domains like slide generation.", "popularity": {"value": 1796, "label": "stars"}, "url": "https://github.com/llmsresearch/paperbanana", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:martineux/dvine82-xl", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "martineux/dvine82-xl", "date": "2026-02-04", "createdAt": "2026-02-04", "sourceUpdatedAt": "2026-02-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 332224 downloads and tags: diffusers, safetensors, endpoints_compatible, diffusers:StableDiffusionXLPipeline.", "popularity": {"value": 332224, "label": "downloads"}, "url": "https://huggingface.co/martineux/dvine82-xl", "tags": ["diffusers", "diffusers:stablediffusionxlpipeline", "endpoints_compatible", "image-generation", "region:us", "safetensors"]}
{"id": "hf-dataset:jungcow/my_user_data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jungcow/my_user_data", "date": "2026-05-28", "createdAt": "2026-02-03", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 83038 downloads.", "popularity": {"value": 83038, "label": "downloads"}, "url": "https://huggingface.co/datasets/jungcow/my_user_data", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:robert05/3Dbrain", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "robert05/3Dbrain", "date": "2026-05-15", "createdAt": "2026-02-03", "sourceUpdatedAt": "2026-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54832 downloads.", "popularity": {"value": 54832, "label": "downloads"}, "url": "https://huggingface.co/datasets/robert05/3Dbrain", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:utter-project/EuroWeb-2512", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "utter-project/EuroWeb-2512", "date": "2026-02-09", "createdAt": "2026-02-03", "sourceUpdatedAt": "2026-02-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 324214 downloads.", "popularity": {"value": 324214, "label": "downloads"}, "url": "https://huggingface.co/datasets/utter-project/EuroWeb-2512", "tags": ["arxiv:2602.05879", "datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:tabular"]}
{"id": "hf-model:unsloth/Qwen3-Coder-Next-GGUF", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "unsloth/Qwen3-Coder-Next-GGUF", "date": "2026-02-03", "createdAt": "2026-02-03", "sourceUpdatedAt": "2026-02-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3085069 downloads and tags: gguf, qwen3_next, unsloth, qwen.", "popularity": {"value": 3085069, "label": "downloads"}, "url": "https://huggingface.co/unsloth/Qwen3-Coder-Next-GGUF", "tags": ["base_model:quantized:qwen/qwen3-coder-next", "base_model:qwen/qwen3-coder-next", "coding", "gguf", "qwen", "qwen3", "qwen3_next", "text-generation"]}
{"id": "github:hkuds/nanobot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HKUDS/nanobot", "date": "2026-06-04", "createdAt": "2026-02-01", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Lightweight, open-source AI agent for your tools, chats, and workflows.", "popularity": {"value": 43607, "label": "stars"}, "url": "https://github.com/HKUDS/nanobot", "tags": ["agents", "llm"]}
{"id": "github:evomap/evolver", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EvoMap/evolver", "date": "2026-06-03", "createdAt": "2026-02-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai", "popularity": {"value": 7690, "label": "stars"}, "url": "https://github.com/EvoMap/evolver", "tags": ["agents", "ai-agent"]}
{"id": "github:1186258278/openclawchinesetranslation", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "1186258278/OpenClawChineseTranslation", "date": "2026-06-04", "createdAt": "2026-01-30", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🦞 OpenClaw (Clawdbot/Moltbot) 汉化版 - 开源个人 AI 助手中文版 | Claude/ChatGPT LLM 接入 | WhatsApp/Telegram/Discord 多平台 | 每小时自动同步 | CLI + Dashboard 全中文 | 全流程搭建教程，以及排错指南！", "popularity": {"value": 3795, "label": "stars"}, "url": "https://github.com/1186258278/OpenClawChineseTranslation", "tags": ["agents", "ai-agent"]}
{"id": "github:hbai-ltd/toonflow-app", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HBAI-Ltd/Toonflow-app", "date": "2026-06-04", "createdAt": "2026-01-29", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Toonflow 是开源一站式 AI 短剧创作工具，将小说、剧本快速转化为动画短剧。集成 AI 编剧、智能分镜、角色与视频生成，跨平台桌面端轻量部署，助力创作者低成本批量产出视觉内容。Toonflow is an open-source AI tool that turns stories and scripts into animated short dramas. Features AI scriptwriting, storyboarding, character and video generatio...", "popularity": {"value": 9533, "label": "stars"}, "url": "https://github.com/HBAI-Ltd/Toonflow-app", "tags": ["generative-ai", "video-tools"]}
{"id": "github:moltis-org/moltis", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "moltis-org/moltis", "date": "2026-06-03", "createdAt": "2026-01-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and MCP tools. Secure by design, runs on your hardware.", "popularity": {"value": 2721, "label": "stars"}, "url": "https://github.com/moltis-org/moltis", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:facebook/ego-1k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "facebook/ego-1k", "date": "2026-03-17", "createdAt": "2026-01-29", "sourceUpdatedAt": "2026-03-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 84230 downloads.", "popularity": {"value": 84230, "label": "downloads"}, "url": "https://huggingface.co/datasets/facebook/ego-1k", "tags": ["3d-reconstruction", "arxiv:2603.13741", "datasets", "egocentric", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:alexisplacet/adsblol_globe_history", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "alexisplacet/adsblol_globe_history", "date": "2026-02-04", "createdAt": "2026-01-29", "sourceUpdatedAt": "2026-02-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62350 downloads.", "popularity": {"value": 62350, "label": "downloads"}, "url": "https://huggingface.co/datasets/alexisplacet/adsblol_globe_history", "tags": ["adsb", "aviation", "datasets", "flight-tracking", "heatmap", "language:en", "license:odbl", "parquet"]}
{"id": "github:christopherkahler/paul", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ChristopherKahler/paul", "date": "2026-06-03", "createdAt": "2026-01-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Plan-Apply-Unify Loop — Structured AI-assisted development for Claude Code. Quality over speed-for-speed's-sake.", "popularity": {"value": 961, "label": "stars"}, "url": "https://github.com/ChristopherKahler/paul", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-model:Qwen/Qwen3-ASR-1.7B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-ASR-1.7B", "date": "2026-01-28", "createdAt": "2026-01-28", "sourceUpdatedAt": "2026-01-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1899089 downloads and tags: safetensors, qwen3_asr, automatic-speech-recognition, arxiv:2601.21337.", "popularity": {"value": 1899089, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-ASR-1.7B", "tags": ["arxiv:2601.21337", "audio", "automatic-speech-recognition", "deploy:azure", "eval-results", "license:apache-2.0", "qwen3_asr", "region:us"]}
{"id": "github:jmuncor/tokentap", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jmuncor/tokentap", "date": "2026-04-03", "createdAt": "2026-01-27", "sourceUpdatedAt": "2026-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Intercept LLM API traffic and visualize token usage in a real-time terminal dashboard. Track costs,       debug prompts, and monitor context window usage across your AI development sessions.", "popularity": {"value": 797, "label": "stars"}, "url": "https://github.com/jmuncor/tokentap", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:jo-inc/camofox-browser", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jo-inc/camofox-browser", "date": "2026-06-03", "createdAt": "2026-01-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.", "popularity": {"value": 6295, "label": "stars"}, "url": "https://github.com/jo-inc/camofox-browser", "tags": ["agents", "ai-agent"]}
{"id": "github:evoscientist/evoscientist", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EvoScientist/EvoScientist", "date": "2026-06-03", "createdAt": "2026-01-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔬 Harness Vibe Research with Self-evolving AI Scientists", "popularity": {"value": 3316, "label": "stars"}, "url": "https://github.com/EvoScientist/EvoScientist", "tags": ["agents", "ai-agent"]}
{"id": "github:tabularisdb/tabularis", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "TabularisDB/tabularis", "date": "2026-06-03", "createdAt": "2026-01-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A lightweight, cross-platform database client for developers. Supports MySQL, PostgreSQL and SQLite. Hackable with plugins. Built for speed, security, and aesthetics.", "popularity": {"value": 2247, "label": "stars"}, "url": "https://github.com/TabularisDB/tabularis", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:AIencoder/llama-cpp-wheels", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AIencoder/llama-cpp-wheels", "date": "2026-05-02", "createdAt": "2026-01-25", "sourceUpdatedAt": "2026-05-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50476 downloads.", "popularity": {"value": 50476, "label": "downloads"}, "url": "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels", "tags": ["binary", "code", "datasets", "doi:10.57967/hf/7756", "language:en", "license:mit", "linux", "llama-cpp"]}
{"id": "github:endee-io/endee", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "endee-io/endee", "date": "2026-06-02", "createdAt": "2026-01-24", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/", "popularity": {"value": 1309, "label": "stars"}, "url": "https://github.com/endee-io/endee", "tags": ["vector-database", "vector-db"]}
{"id": "hf-dataset:obiwan96/endless-terminals", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "obiwan96/endless-terminals", "date": "2026-01-24", "createdAt": "2026-01-24", "sourceUpdatedAt": "2026-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 97735 downloads.", "popularity": {"value": 97735, "label": "downloads"}, "url": "https://huggingface.co/datasets/obiwan96/endless-terminals", "tags": ["datasets", "region:us"]}
{"id": "github:santifer/cv-santiago", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "santifer/cv-santiago", "date": "2026-06-02", "createdAt": "2026-01-23", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Interactive CV with AI chat integration. Built with React 19, TypeScript, Claude API. Chat with my AI avatar about my experience.", "popularity": {"value": 621, "label": "stars"}, "url": "https://github.com/santifer/cv-santiago", "tags": ["llmops", "tools"]}
{"id": "hf-dataset:bettergovph/gov-library", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bettergovph/gov-library", "date": "2026-01-31", "createdAt": "2026-01-23", "sourceUpdatedAt": "2026-01-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 98297 downloads.", "popularity": {"value": 98297, "label": "downloads"}, "url": "https://huggingface.co/datasets/bettergovph/gov-library", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:tabular", "modality:text"]}
{"id": "github:rtk-ai/rtk", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "rtk-ai/rtk", "date": "2026-06-03", "createdAt": "2026-01-22", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. Single Rust binary, zero dependencies", "popularity": {"value": 58490, "label": "stars"}, "url": "https://github.com/rtk-ai/rtk", "tags": ["developer-tools", "llm"]}
{"id": "github:mac-automl/mindpipe", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MAC-AutoML/MindPipe", "date": "2026-06-03", "createdAt": "2026-01-22", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A powerful model compression framework for LLMs and LVLMs, adapted for NVIDIA GPUs and Huawei Ascend NPUs.", "popularity": {"value": 1006, "label": "stars"}, "url": "https://github.com/MAC-AutoML/MindPipe", "tags": ["evaluation"]}
{"id": "github:waooai/waoowaoo", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "waooAI/waoowaoo", "date": "2026-06-02", "createdAt": "2026-01-22", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "首家工业级全流程 AI 影视生产平台。Industry-first professional AI Agent platform for controllable film & video production. From shorts to live-action with Hollywood-standard workflows.", "popularity": {"value": 12547, "label": "stars"}, "url": "https://github.com/waooAI/waoowaoo", "tags": ["ai-agent", "video-tools"]}
{"id": "hf-dataset:akasheroor/American-Sign-Language-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "akasheroor/American-Sign-Language-Dataset", "date": "2026-01-22", "createdAt": "2026-01-22", "sourceUpdatedAt": "2026-01-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 109691 downloads.", "popularity": {"value": 109691, "label": "downloads"}, "url": "https://huggingface.co/datasets/akasheroor/American-Sign-Language-Dataset", "tags": ["american sign language", "asl", "datasets", "gesture recognition", "library:datasets", "library:mlcroissant", "license:mit", "modality:video"]}
{"id": "hf-model:Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice", "date": "2026-01-21", "createdAt": "2026-01-21", "sourceUpdatedAt": "2026-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1913801 downloads and tags: safetensors, qwen3_tts, text-to-speech, arxiv:2601.15621.", "popularity": {"value": 1913801, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice", "tags": ["arxiv:2601.15621", "audio", "license:apache-2.0", "qwen3_tts", "region:us", "safetensors", "text-to-speech"]}
{"id": "hf-model:Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice", "date": "2026-01-21", "createdAt": "2026-01-21", "sourceUpdatedAt": "2026-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 928555 downloads and tags: safetensors, qwen3_tts, tts, qwen.", "popularity": {"value": 928555, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice", "tags": ["audio", "en", "qwen", "qwen3_tts", "safetensors", "text-to-speech", "tts", "zh"]}
{"id": "hf-model:Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign", "date": "2026-01-21", "createdAt": "2026-01-21", "sourceUpdatedAt": "2026-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 736556 downloads and tags: qwen-tts, safetensors, qwen3_tts, audio.", "popularity": {"value": 736556, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign", "tags": ["audio", "multilingual", "qwen", "qwen-tts", "qwen3_tts", "safetensors", "text-to-speech", "tts"]}
{"id": "hf-model:Qwen/Qwen3-TTS-12Hz-0.6B-Base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-TTS-12Hz-0.6B-Base", "date": "2026-01-21", "createdAt": "2026-01-21", "sourceUpdatedAt": "2026-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 730686 downloads and tags: safetensors, qwen3_tts, audio, tts.", "popularity": {"value": 730686, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base", "tags": ["audio", "en", "qwen3_tts", "safetensors", "text-to-speech", "tts", "voice-clone", "zh"]}
{"id": "github:christopherkarani/wax", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "christopherkarani/Wax", "date": "2026-05-24", "createdAt": "2026-01-20", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Single-file memory layer for AI agents, sub mili-second RAG on Apple Silicon. Metal Optimized On-Device. No Server. No API. One File. Pure Swift", "popularity": {"value": 753, "label": "stars"}, "url": "https://github.com/christopherkarani/Wax", "tags": ["agents", "vector-database"]}
{"id": "github:hmbown/codewhale", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Hmbown/CodeWhale", "date": "2026-06-03", "createdAt": "2026-01-19", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "DeepSeek + MiMo coding agent in terminal", "popularity": {"value": 36915, "label": "stars"}, "url": "https://github.com/Hmbown/CodeWhale", "tags": ["agents", "llm"]}
{"id": "github:dadbodgeoff/drift", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dadbodgeoff/drift", "date": "2026-05-31", "createdAt": "2026-01-19", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI.", "popularity": {"value": 782, "label": "stars"}, "url": "https://github.com/dadbodgeoff/drift", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:Maynor996/upload2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Maynor996/upload2", "date": "2026-05-29", "createdAt": "2026-01-19", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 921570 downloads.", "popularity": {"value": 921570, "label": "downloads"}, "url": "https://huggingface.co/datasets/Maynor996/upload2", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:Maynor996/img_upload", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Maynor996/img_upload", "date": "2026-05-29", "createdAt": "2026-01-19", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 855254 downloads.", "popularity": {"value": 855254, "label": "downloads"}, "url": "https://huggingface.co/datasets/Maynor996/img_upload", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:google/WaxalNLP", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google/WaxalNLP", "date": "2026-05-05", "createdAt": "2026-01-19", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51351 downloads.", "popularity": {"value": 51351, "label": "downloads"}, "url": "https://huggingface.co/datasets/google/WaxalNLP", "tags": ["arxiv:2602.02734", "audio", "automatic-speech-recognition", "datasets", "format:parquet", "language:ach", "language:aka", "language:amh"]}
{"id": "github:affaan-m/ecc", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "affaan-m/ECC", "date": "2026-06-03", "createdAt": "2026-01-18", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.", "popularity": {"value": 205905, "label": "stars"}, "url": "https://github.com/affaan-m/ECC", "tags": ["agents", "llm"]}
{"id": "github:resciencelab/opc-skills", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ReScienceLab/opc-skills", "date": "2026-06-03", "createdAt": "2026-01-17", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Agent Skills for Solopreneurs", "popularity": {"value": 911, "label": "stars"}, "url": "https://github.com/ReScienceLab/opc-skills", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:Cyberpluis/essential-web-1t-sample-fdc-partitioned", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Cyberpluis/essential-web-1t-sample-fdc-partitioned", "date": "2026-01-17", "createdAt": "2026-01-17", "sourceUpdatedAt": "2026-01-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70386 downloads.", "popularity": {"value": 70386, "label": "downloads"}, "url": "https://huggingface.co/datasets/Cyberpluis/essential-web-1t-sample-fdc-partitioned", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:apache-2.0", "modality:text"]}
{"id": "github:lsdefine/genericagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lsdefine/GenericAgent", "date": "2026-06-02", "createdAt": "2026-01-16", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption", "popularity": {"value": 12503, "label": "stars"}, "url": "https://github.com/lsdefine/GenericAgent", "tags": ["agents", "ai-agent"]}
{"id": "github:q00/ouroboros", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Q00/ouroboros", "date": "2026-06-04", "createdAt": "2026-01-14", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Agent OS: Stop prompting. Start specifying.", "popularity": {"value": 4430, "label": "stars"}, "url": "https://github.com/Q00/ouroboros", "tags": ["agents", "ai-agent"]}
{"id": "github:opencoworkai/open-cowork", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "OpenCoworkAI/open-cowork", "date": "2026-06-03", "createdAt": "2026-01-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source AI agent desktop app for Windows & macOS. One-click install Claude Code, MCP tools, and Skills — with sandbox isolation, multi-model support, and Feishu/Slack integration.", "popularity": {"value": 1489, "label": "stars"}, "url": "https://github.com/OpenCoworkAI/open-cowork", "tags": ["agents", "ai-tools"]}
{"id": "github:geekjourneyx/md2wechat-skill", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "geekjourneyx/md2wechat-skill", "date": "2026-05-28", "createdAt": "2026-01-11", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Markdown to WeChat CLI | 一键排版发布到微信公众号：支持 40+ 排版样式和专业主题 、AI 配图 、批量发布", "popularity": {"value": 2704, "label": "stars"}, "url": "https://github.com/geekjourneyx/md2wechat-skill", "tags": ["agents", "ai-agent"]}
{"id": "github:zhulinsen/daily_stock_analysis", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ZhuLinsen/daily_stock_analysis", "date": "2026-06-04", "createdAt": "2026-01-10", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LLM驱动的 A/H/美股智能分析：多数据源行情 + 实时新闻 + LLM决策仪表盘 + 多渠道推送，零成本定时运行，纯白嫖. LLM-powered stock analysis system for A/H/US markets.", "popularity": {"value": 40330, "label": "stars"}, "url": "https://github.com/ZhuLinsen/daily_stock_analysis", "tags": ["llm", "tools"]}
{"id": "github:agavra/tuicr", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "agavra/tuicr", "date": "2026-06-03", "createdAt": "2026-01-08", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "a code review TUI with vim keybindings", "popularity": {"value": 878, "label": "stars"}, "url": "https://github.com/agavra/tuicr", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:chopratejas/headroom", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "chopratejas/headroom", "date": "2026-06-03", "createdAt": "2026-01-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.", "popularity": {"value": 10083, "label": "stars"}, "url": "https://github.com/chopratejas/headroom", "tags": ["rag"]}
{"id": "hf-dataset:UniverseTBD/mmu_gaia_gaia", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "UniverseTBD/mmu_gaia_gaia", "date": "2026-05-20", "createdAt": "2026-01-07", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 116363 downloads.", "popularity": {"value": 116363, "label": "downloads"}, "url": "https://huggingface.co/datasets/UniverseTBD/mmu_gaia_gaia", "tags": ["arxiv:2412.02527", "astronomy", "datasets", "license:cc-by-4.0", "region:us", "size_categories:100m<n<1b"]}
{"id": "hf-model:Qwen/Qwen3-VL-Embedding-8B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-VL-Embedding-8B", "date": "2026-01-07", "createdAt": "2026-01-07", "sourceUpdatedAt": "2026-01-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1562703 downloads and tags: sentence-transformers, safetensors, qwen3_vl, image-text-to-text.", "popularity": {"value": 1562703, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B", "tags": ["embedding", "embeddings", "image-text-to-text", "multimodal embedding", "qwen", "qwen3_vl", "safetensors", "sentence-transformers"]}
{"id": "hf-dataset:Saberlve/bridgev2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Saberlve/bridgev2", "date": "2026-01-07", "createdAt": "2026-01-07", "sourceUpdatedAt": "2026-01-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67881 downloads.", "popularity": {"value": 67881, "label": "downloads"}, "url": "https://huggingface.co/datasets/Saberlve/bridgev2", "tags": ["bridgev2", "datasets", "lerobot", "license:apache-2.0", "openx", "region:us", "task_categories:robotics"]}
{"id": "hf-dataset:KarlQuant/k1rl-checkpoints", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "KarlQuant/k1rl-checkpoints", "date": "2026-06-04", "createdAt": "2026-01-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 109836 downloads.", "popularity": {"value": 109836, "label": "downloads"}, "url": "https://huggingface.co/datasets/KarlQuant/k1rl-checkpoints", "tags": ["datasets", "region:us"]}
{"id": "github:volcengine/openviking", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "volcengine/OpenViking", "date": "2026-06-03", "createdAt": "2026-01-05", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context...", "popularity": {"value": 25106, "label": "stars"}, "url": "https://github.com/volcengine/OpenViking", "tags": ["agents", "llm"]}
{"id": "github:lightricks/ltx-2", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Lightricks/LTX-2", "date": "2026-05-28", "createdAt": "2026-01-03", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.", "popularity": {"value": 7085, "label": "stars"}, "url": "https://github.com/Lightricks/LTX-2", "tags": ["generative-ai", "video-tools"]}
{"id": "github:natfii/unrealclaude", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Natfii/UnrealClaude", "date": "2026-05-16", "createdAt": "2026-01-03", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Claude Code CLI integration for Unreal Engine 5.7 - Get AI coding assistance with built-in UE5.7 documentation context directly in the editor.", "popularity": {"value": 659, "label": "stars"}, "url": "https://github.com/Natfii/UnrealClaude", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:can1357/oh-my-pi", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "can1357/oh-my-pi", "date": "2026-06-04", "createdAt": "2025-12-31", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "⌥  AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more", "popularity": {"value": 10325, "label": "stars"}, "url": "https://github.com/can1357/oh-my-pi", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:genrobot2025/10Kh-RealOmin-OpenData", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "genrobot2025/10Kh-RealOmin-OpenData", "date": "2026-04-24", "createdAt": "2025-12-31", "sourceUpdatedAt": "2026-04-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 189527 downloads.", "popularity": {"value": 189527, "label": "downloads"}, "url": "https://huggingface.co/datasets/genrobot2025/10Kh-RealOmin-OpenData", "tags": ["agent", "datasets", "dual-arm", "embodied intelligence", "language:en", "language:zh", "license:cc-by-sa-4.0", "modality:video"]}
{"id": "hf-dataset:nvidia/SAGE-10k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/SAGE-10k", "date": "2026-02-11", "createdAt": "2025-12-31", "sourceUpdatedAt": "2026-02-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 75060 downloads.", "popularity": {"value": 75060, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/SAGE-10k", "tags": ["arxiv:2602.10116", "datasets", "embodied-ai", "interactive-scenes", "language:en", "license:apache-2.0", "region:us", "robotics"]}
{"id": "github:hkuds/deeptutor", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HKUDS/DeepTutor", "date": "2026-05-29", "createdAt": "2025-12-28", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "DeepTutor: Agent-native, Open-sourced Personalized Tutoring. https://deeptutor.info/.", "popularity": {"value": 24523, "label": "stars"}, "url": "https://github.com/HKUDS/DeepTutor", "tags": ["agents", "rag"]}
{"id": "github:nguyenphutrong/quotio", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nguyenphutrong/quotio", "date": "2026-06-03", "createdAt": "2025-12-24", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Stop juggling AI accounts. Quotio is a beautiful native macOS menu bar app that unifies your Claude, Gemini, OpenAI, Qwen, and Antigravity subscriptions – with real-time quota tracking and smart auto-failover for AI coding tools like Claude Code, OpenCode,...", "popularity": {"value": 4445, "label": "stars"}, "url": "https://github.com/nguyenphutrong/quotio", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:miscusi-peek/cheatengine-mcp-bridge", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "miscusi-peek/cheatengine-mcp-bridge", "date": "2026-05-26", "createdAt": "2025-12-24", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Connect Cursor, Copilot & Claude AI directly to Cheat Engine via MCP. Automate reverse engineering, pointer scanning, and memory analysis using natural language.", "popularity": {"value": 794, "label": "stars"}, "url": "https://github.com/miscusi-peek/cheatengine-mcp-bridge", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:harborframework/parity-experiments", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "harborframework/parity-experiments", "date": "2026-04-22", "createdAt": "2025-12-24", "sourceUpdatedAt": "2026-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 61750 downloads.", "popularity": {"value": 61750, "label": "downloads"}, "url": "https://huggingface.co/datasets/harborframework/parity-experiments", "tags": ["datasets", "region:us"]}
{"id": "github:skillmatic-ai/awesome-agent-skills", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "skillmatic-ai/awesome-agent-skills", "date": "2026-05-14", "createdAt": "2025-12-22", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The definitive resource for Agent Skills - modular capabilities revolutionizing AI agent architecture", "popularity": {"value": 585, "label": "stars"}, "url": "https://github.com/skillmatic-ai/awesome-agent-skills", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:permutans/arxiv-papers-by-subject", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "permutans/arxiv-papers-by-subject", "date": "2025-12-21", "createdAt": "2025-12-20", "sourceUpdatedAt": "2025-12-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 495530 downloads.", "popularity": {"value": 495530, "label": "downloads"}, "url": "https://huggingface.co/datasets/permutans/arxiv-papers-by-subject", "tags": ["academic-papers", "arxiv", "datasets", "language:en", "license:mit", "metadata", "region:us", "research"]}
{"id": "github:alibaba/opensandbox", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alibaba/OpenSandbox", "date": "2026-06-04", "createdAt": "2025-12-17", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Secure, Fast, and Extensible Sandbox runtime for AI agents.", "popularity": {"value": 11200, "label": "stars"}, "url": "https://github.com/alibaba/OpenSandbox", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:sunghong/CADS-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sunghong/CADS-dataset", "date": "2025-12-17", "createdAt": "2025-12-17", "sourceUpdatedAt": "2025-12-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 93350 downloads.", "popularity": {"value": 93350, "label": "downloads"}, "url": "https://huggingface.co/datasets/sunghong/CADS-dataset", "tags": ["3d", "anatomy", "arxiv:2507.22953", "ct", "datasets", "format:csv", "image", "library:datasets"]}
{"id": "hf-dataset:Chelsea707/arxiv-cs-2020-2025-pdfs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Chelsea707/arxiv-cs-2020-2025-pdfs", "date": "2025-12-23", "createdAt": "2025-12-16", "sourceUpdatedAt": "2025-12-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 350308 downloads.", "popularity": {"value": 350308, "label": "downloads"}, "url": "https://huggingface.co/datasets/Chelsea707/arxiv-cs-2020-2025-pdfs", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:stair-lab/nonmyopia_results", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "stair-lab/nonmyopia_results", "date": "2026-02-17", "createdAt": "2025-12-15", "sourceUpdatedAt": "2026-02-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63056 downloads.", "popularity": {"value": 63056, "label": "downloads"}, "url": "https://huggingface.co/datasets/stair-lab/nonmyopia_results", "tags": ["datasets", "region:us"]}
{"id": "hf-model:frankjoshua/novaAnimeXL_ilV140", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "frankjoshua/novaAnimeXL_ilV140", "date": "2025-12-13", "createdAt": "2025-12-13", "sourceUpdatedAt": "2025-12-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 447216 downloads and tags: diffusers, safetensors, endpoints_compatible, diffusers:StableDiffusionXLPipeline.", "popularity": {"value": 447216, "label": "downloads"}, "url": "https://huggingface.co/frankjoshua/novaAnimeXL_ilV140", "tags": ["diffusers", "diffusers:stablediffusionxlpipeline", "endpoints_compatible", "image-generation", "region:us", "safetensors"]}
{"id": "github:hugohe3/ppt-master", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "hugohe3/ppt-master", "date": "2026-06-04", "createdAt": "2025-12-10", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI generates a real, editable PowerPoint from any document — native shapes & animations, speaker notes voiced as audio narration, and the option to follow your own .pptx template, not slide images · by Hugo He", "popularity": {"value": 24138, "label": "stars"}, "url": "https://github.com/hugohe3/ppt-master", "tags": ["ai-agent", "video-tools"]}
{"id": "hf-dataset:CARD-Data/CARD-Italy", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CARD-Data/CARD-Italy", "date": "2026-05-16", "createdAt": "2025-12-09", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 136000 downloads.", "popularity": {"value": 136000, "label": "downloads"}, "url": "https://huggingface.co/datasets/CARD-Data/CARD-Italy", "tags": ["autonomous-driving", "computer-vision", "datasets", "depth", "license:cc-by-nc-4.0", "lidar", "modality:image", "modality:text"]}
{"id": "github:cporter202/api-mega-list", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "cporter202/API-mega-list", "date": "2026-01-27", "createdAt": "2025-12-09", "sourceUpdatedAt": "2026-01-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "This GitHub repo is a powerhouse collection of APIs you can start using immediately to build everything from simple automations to full-scale applications. One of the most valuable API lists on GitHub—period. 💪", "popularity": {"value": 5765, "label": "stars"}, "url": "https://github.com/cporter202/API-mega-list", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:Bover/fineweb", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Bover/fineweb", "date": "2025-12-08", "createdAt": "2025-12-08", "sourceUpdatedAt": "2025-12-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 57153 downloads.", "popularity": {"value": 57153, "label": "downloads"}, "url": "https://huggingface.co/datasets/Bover/fineweb", "tags": ["arxiv:2109.07445", "arxiv:2306.01116", "arxiv:2406.17557", "datasets", "language:en", "license:odc-by", "region:us", "size_categories:n>1t"]}
{"id": "github:boxlite-ai/boxlite", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "boxlite-ai/boxlite", "date": "2026-06-03", "createdAt": "2025-12-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Compute substrate for AI agents: lightweight enough to live on your laptop, elastic enough to scale into the cloud and unleash unlimited resources.", "popularity": {"value": 2107, "label": "stars"}, "url": "https://github.com/boxlite-ai/boxlite", "tags": ["agents", "ai-agent"]}
{"id": "github:orneryd/nornicdb", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "orneryd/NornicDB", "date": "2026-06-04", "createdAt": "2025-12-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, manag...", "popularity": {"value": 763, "label": "stars"}, "url": "https://github.com/orneryd/NornicDB", "tags": ["vector-database", "vector-db"]}
{"id": "github:waybarrios/vllm-mlx", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "waybarrios/vllm-mlx", "date": "2026-05-31", "createdAt": "2025-12-06", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenAI and Anthropic compatible server for Apple Silicon. Run LLMs and vision-language models (Llama, Qwen-VL, LLaVA) with continuous batching, MCP tool calling, and multimodal support. Native MLX backend, 400+ tok/s. Works with Claude Code.", "popularity": {"value": 1298, "label": "stars"}, "url": "https://github.com/waybarrios/vllm-mlx", "tags": ["inference"]}
{"id": "github:alibaba/zvec", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alibaba/zvec", "date": "2026-06-03", "createdAt": "2025-12-05", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A lightweight, lightning-fast, in-process vector database", "popularity": {"value": 9748, "label": "stars"}, "url": "https://github.com/alibaba/zvec", "tags": ["rag", "vector-db"]}
{"id": "hf-dataset:builddotai/Egocentric-100K", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "builddotai/Egocentric-100K", "date": "2026-02-16", "createdAt": "2025-12-04", "sourceUpdatedAt": "2026-02-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 78241 downloads.", "popularity": {"value": 78241, "label": "downloads"}, "url": "https://huggingface.co/datasets/builddotai/Egocentric-100K", "tags": ["datasets", "egocentric", "format:webdataset", "library:datasets", "library:mlcroissant", "library:webdataset", "license:apache-2.0", "modality:text"]}
{"id": "hf-model:microsoft/VibeVoice-Realtime-0.5B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/VibeVoice-Realtime-0.5B", "date": "2025-12-04", "createdAt": "2025-12-04", "sourceUpdatedAt": "2025-12-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 804623 downloads and tags: transformers, safetensors, vibevoice_streaming, Realtime TTS.", "popularity": {"value": 804623, "label": "downloads"}, "url": "https://huggingface.co/microsoft/VibeVoice-Realtime-0.5B", "tags": ["audio", "en", "long-form speech generation", "realtime tts", "safetensors", "streaming text input", "text-to-speech", "transformers"]}
{"id": "github:asheshgoplani/agent-deck", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "asheshgoplani/agent-deck", "date": "2026-06-04", "createdAt": "2025-12-03", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Terminal session manager for AI coding agents. One TUI for Claude, Gemini, OpenCode, Codex, and more.", "popularity": {"value": 2609, "label": "stars"}, "url": "https://github.com/asheshgoplani/agent-deck", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:CARD-Data/CARD-Germany-Batch3", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CARD-Data/CARD-Germany-Batch3", "date": "2026-05-16", "createdAt": "2025-12-02", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 152046 downloads.", "popularity": {"value": 152046, "label": "downloads"}, "url": "https://huggingface.co/datasets/CARD-Data/CARD-Germany-Batch3", "tags": ["autonomous-driving", "computer-vision", "datasets", "depth", "license:cc-by-4.0", "lidar", "modality:image", "modality:text"]}
{"id": "hf-model:deepseek-ai/DeepSeek-V3.2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "deepseek-ai/DeepSeek-V3.2", "date": "2025-12-01", "createdAt": "2025-12-01", "sourceUpdatedAt": "2025-12-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4279677 downloads and tags: transformers, safetensors, deepseek_v32, text-generation.", "popularity": {"value": 4279677, "label": "downloads"}, "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2", "tags": ["base_model:deepseek-ai/deepseek-v3.2-exp-base", "base_model:finetune:deepseek-ai/deepseek-v3.2-exp-base", "conversational", "deepseek_v32", "license:mit", "llm", "safetensors", "text-generation"]}
{"id": "hf-dataset:FastVideo/Wan-Syn_77x448x832_600k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "FastVideo/Wan-Syn_77x448x832_600k", "date": "2025-12-27", "createdAt": "2025-11-27", "sourceUpdatedAt": "2025-12-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55293 downloads.", "popularity": {"value": 55293, "label": "downloads"}, "url": "https://huggingface.co/datasets/FastVideo/Wan-Syn_77x448x832_600k", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "github:chatlab/chatlab", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ChatLab/ChatLab", "date": "2026-06-03", "createdAt": "2025-11-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Local-first chat history analyzer with AI. | 本地优先的 AI 聊天记录分析工具", "popularity": {"value": 6584, "label": "stars"}, "url": "https://github.com/ChatLab/ChatLab", "tags": ["agents", "ai-agent"]}
{"id": "github:hismax/redink", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HisMax/RedInk", "date": "2026-03-17", "createdAt": "2025-11-25", "sourceUpdatedAt": "2026-03-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Red Ink - A one-stop Xiaohongshu image-and-text generator based on the 🍌Nano Banana Pro🍌, \"One Sentence, One Image: Generate Xiaohongshu Text and Images.\"", "popularity": {"value": 5299, "label": "stars"}, "url": "https://github.com/HisMax/RedInk", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:nvidia/Nemotron-Pretraining-Code-v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/Nemotron-Pretraining-Code-v2", "date": "2025-12-22", "createdAt": "2025-11-25", "sourceUpdatedAt": "2025-12-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 91923 downloads.", "popularity": {"value": 91923, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/Nemotron-Pretraining-Code-v2", "tags": ["arxiv:2412.02595", "arxiv:2505.02881", "arxiv:2508.14444", "arxiv:2508.15096", "datasets", "format:parquet", "library:dask", "library:datasets"]}
{"id": "hf-model:Tongyi-MAI/Z-Image-Turbo", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Tongyi-MAI/Z-Image-Turbo", "date": "2025-11-25", "createdAt": "2025-11-25", "sourceUpdatedAt": "2025-11-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1005608 downloads and tags: diffusers, safetensors, text-to-image, en.", "popularity": {"value": 1005608, "label": "downloads"}, "url": "https://huggingface.co/Tongyi-MAI/Z-Image-Turbo", "tags": ["arxiv:2511.13649", "arxiv:2511.22677", "arxiv:2511.22699", "diffusers", "en", "image-generation", "license:apache-2.0", "safetensors"]}
{"id": "hf-dataset:allenai/dolma3_mix-6T", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/dolma3_mix-6T", "date": "2026-01-15", "createdAt": "2025-11-24", "sourceUpdatedAt": "2026-01-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 69113 downloads.", "popularity": {"value": 69113, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/dolma3_mix-6T", "tags": ["arxiv:2512.13961", "datasets", "language:en", "license:odc-by", "region:us", "task_categories:text-generation"]}
{"id": "github:runmaestro/maestro", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "RunMaestro/Maestro", "date": "2026-06-04", "createdAt": "2025-11-23", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Agent Orchestration Command Center", "popularity": {"value": 2975, "label": "stars"}, "url": "https://github.com/RunMaestro/Maestro", "tags": ["agents", "generative-ai"]}
{"id": "github:foxhui/webai2api", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "foxhui/WebAI2API", "date": "2026-04-23", "createdAt": "2025-11-23", "sourceUpdatedAt": "2026-04-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "WebAI2API: 基于 Camoufox 的网页 AI 转 API 工具，支持 LMArena/Gemini等，多窗口并发与账号隔离。 | Web AI to OpenAI API via Camoufox. Supports LMArena/Gemini and more, multi-window concurrency & account isolation.", "popularity": {"value": 977, "label": "stars"}, "url": "https://github.com/foxhui/WebAI2API", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:gradio/frontend", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gradio/frontend", "date": "2026-06-03", "createdAt": "2025-11-18", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52638 downloads.", "popularity": {"value": 52638, "label": "downloads"}, "url": "https://huggingface.co/datasets/gradio/frontend", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:CARD-Data/CARD-Germany-Batch2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CARD-Data/CARD-Germany-Batch2", "date": "2026-05-16", "createdAt": "2025-11-18", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48189 downloads.", "popularity": {"value": 48189, "label": "downloads"}, "url": "https://huggingface.co/datasets/CARD-Data/CARD-Germany-Batch2", "tags": ["autonomous-driving", "computer-vision", "datasets", "depth", "license:cc-by-4.0", "lidar", "modality:image", "modality:text"]}
{"id": "hf-dataset:LejuRobotics/LET-Base-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "LejuRobotics/LET-Base-Dataset", "date": "2026-04-15", "createdAt": "2025-11-12", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52113 downloads.", "popularity": {"value": 52113, "label": "downloads"}, "url": "https://huggingface.co/datasets/LejuRobotics/LET-Base-Dataset", "tags": ["datasets", "license:cc-by-nc-sa-4.0", "region:us"]}
{"id": "hf-dataset:Knowing/f4_re", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Knowing/f4_re", "date": "2025-11-11", "createdAt": "2025-11-11", "sourceUpdatedAt": "2025-11-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 47740 downloads.", "popularity": {"value": 47740, "label": "downloads"}, "url": "https://huggingface.co/datasets/Knowing/f4_re", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:chrisrca/clash-royale-tv-replays", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "chrisrca/clash-royale-tv-replays", "date": "2025-12-09", "createdAt": "2025-11-10", "sourceUpdatedAt": "2025-12-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51569 downloads.", "popularity": {"value": 51569, "label": "downloads"}, "url": "https://huggingface.co/datasets/chrisrca/clash-royale-tv-replays", "tags": ["clash-royale", "computer-vision", "datasets", "gaming", "image-dataset", "license:mit", "mobile-gaming", "modality:image"]}
{"id": "hf-dataset:malcolmrey/samples", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "malcolmrey/samples", "date": "2026-05-06", "createdAt": "2025-11-09", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49572 downloads.", "popularity": {"value": 49572, "label": "downloads"}, "url": "https://huggingface.co/datasets/malcolmrey/samples", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:cc0-1.0", "modality:image", "region:us", "size_categories:1k<n<10k"]}
{"id": "hf-dataset:nyu-visionx/Cambrian-S-3M", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nyu-visionx/Cambrian-S-3M", "date": "2026-01-22", "createdAt": "2025-11-07", "sourceUpdatedAt": "2026-01-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 72047 downloads.", "popularity": {"value": 72047, "label": "downloads"}, "url": "https://huggingface.co/datasets/nyu-visionx/Cambrian-S-3M", "tags": ["arxiv:2511.04670", "datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:htriedman/grokipedia-v0.1-dump", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "htriedman/grokipedia-v0.1-dump", "date": "2025-11-14", "createdAt": "2025-11-06", "sourceUpdatedAt": "2025-11-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55291 downloads.", "popularity": {"value": 55291, "label": "downloads"}, "url": "https://huggingface.co/datasets/htriedman/grokipedia-v0.1-dump", "tags": ["arxiv:2511.09685", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "github:davialabs/davia", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "davialabs/davia", "date": "2026-01-19", "createdAt": "2025-11-05", "sourceUpdatedAt": "2026-01-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Interactive, editable docs designed for coding agents", "popularity": {"value": 1635, "label": "stars"}, "url": "https://github.com/davialabs/davia", "tags": ["agents", "ai-tools"]}
{"id": "github:adongwanai/agentguide", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "adongwanai/AgentGuide", "date": "2026-05-28", "createdAt": "2025-11-03", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成", "popularity": {"value": 5552, "label": "stars"}, "url": "https://github.com/adongwanai/AgentGuide", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:CARD-Data/CARD-Germany-Batch1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CARD-Data/CARD-Germany-Batch1", "date": "2026-05-16", "createdAt": "2025-11-03", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 149510 downloads.", "popularity": {"value": 149510, "label": "downloads"}, "url": "https://huggingface.co/datasets/CARD-Data/CARD-Germany-Batch1", "tags": ["autonomous-driving", "computer-vision", "datasets", "depth", "license:cc-by-4.0", "lidar", "modality:image", "modality:text"]}
{"id": "hf-dataset:lyk/ArxivMetaData", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lyk/ArxivMetaData", "date": "2026-01-08", "createdAt": "2025-10-30", "sourceUpdatedAt": "2026-01-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 120660 downloads.", "popularity": {"value": 120660, "label": "downloads"}, "url": "https://huggingface.co/datasets/lyk/ArxivMetaData", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "hf-model:amazon/chronos-2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "amazon/chronos-2", "date": "2025-10-30", "createdAt": "2025-10-30", "sourceUpdatedAt": "2025-10-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 13412418 downloads and tags: chronos-forecasting, safetensors, t5, time series.", "popularity": {"value": 13412418, "label": "downloads"}, "url": "https://huggingface.co/amazon/chronos-2", "tags": ["chronos-forecasting", "forecasting", "foundation models", "llm", "pretrained models", "safetensors", "t5", "time series"]}
{"id": "github:evermind-ai/everos", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EverMind-AI/EverOS", "date": "2026-06-04", "createdAt": "2025-10-28", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Self-evolving memory across Agent and platform.", "popularity": {"value": 6845, "label": "stars"}, "url": "https://github.com/EverMind-AI/EverOS", "tags": ["agents", "rag"]}
{"id": "hf-dataset:OpenMOSS-Team/OmniAction", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "OpenMOSS-Team/OmniAction", "date": "2026-03-27", "createdAt": "2025-10-28", "sourceUpdatedAt": "2026-03-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 160182 downloads.", "popularity": {"value": 160182, "label": "downloads"}, "url": "https://huggingface.co/datasets/OpenMOSS-Team/OmniAction", "tags": ["arxiv:2510.23763", "datasets", "embodied", "language:en", "license:cc-by-nc-4.0", "omni", "region:us", "robotics"]}
{"id": "hf-dataset:jzr99/mesh4d_dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jzr99/mesh4d_dataset", "date": "2025-10-30", "createdAt": "2025-10-28", "sourceUpdatedAt": "2025-10-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 158708 downloads.", "popularity": {"value": 158708, "label": "downloads"}, "url": "https://huggingface.co/datasets/jzr99/mesh4d_dataset", "tags": ["datasets", "region:us"]}
{"id": "github:seemseam/claude_codex_bridge", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SeemSeam/claude_codex_bridge", "date": "2026-06-04", "createdAt": "2025-10-25", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Visible multi-agent CLI teams for Claude, Codex, Gemini, OpenCode, and Droid with project memory and tmux supervision", "popularity": {"value": 2877, "label": "stars"}, "url": "https://github.com/SeemSeam/claude_codex_bridge", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:JZSG/synth_dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "JZSG/synth_dataset", "date": "2025-10-24", "createdAt": "2025-10-24", "sourceUpdatedAt": "2025-10-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66630 downloads.", "popularity": {"value": 66630, "label": "downloads"}, "url": "https://huggingface.co/datasets/JZSG/synth_dataset", "tags": ["datasets", "region:us"]}
{"id": "github:toon-format/toon", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "toon-format/toon", "date": "2026-05-23", "createdAt": "2025-10-22", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🎒 Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware JSON for LLM prompts. Spec, benchmarks, TypeScript SDK.", "popularity": {"value": 24468, "label": "stars"}, "url": "https://github.com/toon-format/toon", "tags": ["evaluation", "llm"]}
{"id": "github:mantoni/beads-ui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mantoni/beads-ui", "date": "2026-04-17", "createdAt": "2025-10-22", "sourceUpdatedAt": "2026-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Local UI for Beads — Collaborate on issues with your coding agent.", "popularity": {"value": 627, "label": "stars"}, "url": "https://github.com/mantoni/beads-ui", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:stai-tuebingen/faiss-smollm", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "stai-tuebingen/faiss-smollm", "date": "2026-01-01", "createdAt": "2025-10-21", "sourceUpdatedAt": "2026-01-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 77172 downloads.", "popularity": {"value": 77172, "label": "downloads"}, "url": "https://huggingface.co/datasets/stai-tuebingen/faiss-smollm", "tags": ["arxiv:2510.27313", "datasets", "format:arrow", "library:datasets", "library:mlcroissant", "license:odc-by", "modality:text", "region:us"]}
{"id": "github:alirezarezvani/claude-code-skill-factory", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alirezarezvani/claude-code-skill-factory", "date": "2025-11-12", "createdAt": "2025-10-21", "sourceUpdatedAt": "2025-11-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Claude Code Skill Factory — A powerful open-source toolkit for building and deploying production-ready Claude Skills, Code Agents, custom Slash Commands, and LLM Prompts at scale. Easily generate structured skill templates, automate workflow integration, an...", "popularity": {"value": 792, "label": "stars"}, "url": "https://github.com/alirezarezvani/claude-code-skill-factory", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:tokyotech-llm/swallow-code-v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tokyotech-llm/swallow-code-v2", "date": "2025-11-08", "createdAt": "2025-10-20", "sourceUpdatedAt": "2025-11-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73603 downloads.", "popularity": {"value": 73603, "label": "downloads"}, "url": "https://huggingface.co/datasets/tokyotech-llm/swallow-code-v2", "tags": ["arxiv:2505.02881", "arxiv:2506.03524", "code", "datasets", "format:json", "language:en", "library:dask", "library:datasets"]}
{"id": "hf-model:lightonai/LightOnOCR-1B-1025", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "lightonai/LightOnOCR-1B-1025", "date": "2025-10-20", "createdAt": "2025-10-20", "sourceUpdatedAt": "2025-10-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 204833 downloads and tags: transformers, safetensors, mistral3, text-generation.", "popularity": {"value": 204833, "label": "downloads"}, "url": "https://huggingface.co/lightonai/LightOnOCR-1B-1025", "tags": ["document-understanding", "mistral3", "multimodal", "ocr", "pdf", "safetensors", "text-generation", "transformers"]}
{"id": "github:caviraoss/openmemory", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "CaviraOSS/OpenMemory", "date": "2026-05-29", "createdAt": "2025-10-19", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.", "popularity": {"value": 4193, "label": "stars"}, "url": "https://github.com/CaviraOSS/OpenMemory", "tags": ["tools", "vector-database"]}
{"id": "github:lackeyjb/playwright-skill", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lackeyjb/playwright-skill", "date": "2025-12-19", "createdAt": "2025-10-19", "sourceUpdatedAt": "2025-12-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Claude Code Skill for browser automation with Playwright. Model-invoked - Claude autonomously writes and executes custom automation for testing and validation.", "popularity": {"value": 2716, "label": "stars"}, "url": "https://github.com/lackeyjb/playwright-skill", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:maxritter/pilot-shell", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "maxritter/pilot-shell", "date": "2026-06-03", "createdAt": "2025-10-18", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "How real engineers run Claude Code and Codex: spec-driven planning, enforced TDD, persistent memory, and quality enforcement on all levels. Make your agents production-ready.", "popularity": {"value": 1737, "label": "stars"}, "url": "https://github.com/maxritter/pilot-shell", "tags": ["agents", "ai-tools"]}
{"id": "github:yusufkaraaslan/skill_seekers", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "yusufkaraaslan/Skill_Seekers", "date": "2026-05-31", "createdAt": "2025-10-17", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Convert documentation websites, GitHub repositories, and PDFs into Claude AI skills with automatic conflict detection", "popularity": {"value": 13925, "label": "stars"}, "url": "https://github.com/yusufkaraaslan/Skill_Seekers", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:mhattingpete/claude-skills-marketplace", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mhattingpete/claude-skills-marketplace", "date": "2026-03-06", "createdAt": "2025-10-17", "sourceUpdatedAt": "2026-03-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Claude Code Skills for software engineering workflows - Git automation, testing, and code review", "popularity": {"value": 593, "label": "stars"}, "url": "https://github.com/mhattingpete/claude-skills-marketplace", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:lakonik/lakonlab", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Lakonik/LakonLab", "date": "2026-06-01", "createdAt": "2025-10-16", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official implementation of AsymFlow, pi-Flow, GMFlow", "popularity": {"value": 431, "label": "stars"}, "url": "https://github.com/Lakonik/LakonLab", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:allenai/dolma3_pool", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/dolma3_pool", "date": "2026-02-24", "createdAt": "2025-10-16", "sourceUpdatedAt": "2026-02-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 77898 downloads.", "popularity": {"value": 77898, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/dolma3_pool", "tags": ["arxiv:2512.13961", "datasets", "language:en", "license:odc-by", "region:us", "task_categories:text-generation"]}
{"id": "hf-dataset:HuggingFaceFW/finepdfs_lang_classification", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/finepdfs_lang_classification", "date": "2025-10-17", "createdAt": "2025-10-16", "sourceUpdatedAt": "2025-10-17", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 51047 downloads.", "popularity": {"value": 51047, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/finepdfs_lang_classification", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular", "region:us"]}
{"id": "hf-model:nvidia/llama-nemotron-embed-1b-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "nvidia/llama-nemotron-embed-1b-v2", "date": "2025-10-16", "createdAt": "2025-10-16", "sourceUpdatedAt": "2025-10-16", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face model with 703449 downloads and tags: sentence-transformers, pytorch, safetensors, llama_bidirec.", "popularity": {"value": 703449, "label": "downloads"}, "url": "https://huggingface.co/nvidia/llama-nemotron-embed-1b-v2", "tags": ["embeddings", "feature-extraction", "llama_bidirec", "pytorch", "retrieval", "safetensors", "sentence-transformers", "text"]}
{"id": "github:kayba-ai/agentic-context-engine", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "kayba-ai/agentic-context-engine", "date": "2026-05-24", "createdAt": "2025-10-15", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai", "popularity": {"value": 2246, "label": "stars"}, "url": "https://github.com/kayba-ai/agentic-context-engine", "tags": ["agents", "ai-tools"]}
{"id": "github:giovannipasq/agentic-rag-for-dummies", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "GiovanniPasq/agentic-rag-for-dummies", "date": "2026-05-17", "createdAt": "2025-10-13", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.", "popularity": {"value": 3375, "label": "stars"}, "url": "https://github.com/GiovanniPasq/agentic-rag-for-dummies", "tags": ["agents", "generative-ai"]}
{"id": "github:fullagent/fulling", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "FullAgent/fulling", "date": "2026-05-22", "createdAt": "2025-10-11", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fulling is an AI-powered Full-stack Engineer Agent. Built with Next.js, Claude, shadcn/ui, and PostgreSQL. Use kubernetes as infra.", "popularity": {"value": 2426, "label": "stars"}, "url": "https://github.com/FullAgent/fulling", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:vyokky/GUI-360", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "vyokky/GUI-360", "date": "2025-12-15", "createdAt": "2025-10-10", "sourceUpdatedAt": "2025-12-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67677 downloads.", "popularity": {"value": 67677, "label": "downloads"}, "url": "https://huggingface.co/datasets/vyokky/GUI-360", "tags": ["arxiv:2511.04307", "datasets", "license:mit", "region:us", "size_categories:1m<n<10m", "task_categories:image-text-to-text"]}
{"id": "hf-dataset:IPEC-COMMUNITY/OpenFly", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/OpenFly", "date": "2025-11-17", "createdAt": "2025-10-10", "sourceUpdatedAt": "2025-11-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 86197 downloads.", "popularity": {"value": 86197, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/OpenFly", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:facebook/SACo-Gold", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "facebook/SACo-Gold", "date": "2025-11-17", "createdAt": "2025-10-08", "sourceUpdatedAt": "2025-11-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 61614 downloads.", "popularity": {"value": 61614, "label": "downloads"}, "url": "https://huggingface.co/datasets/facebook/SACo-Gold", "tags": ["datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:other"]}
{"id": "hf-dataset:Helsinki-NLP/nemotron-cc-translated", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Helsinki-NLP/nemotron-cc-translated", "date": "2026-04-27", "createdAt": "2025-10-07", "sourceUpdatedAt": "2026-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59391 downloads.", "popularity": {"value": 59391, "label": "downloads"}, "url": "https://huggingface.co/datasets/Helsinki-NLP/nemotron-cc-translated", "tags": ["datasets", "format:parquet", "language:bos", "language:bul", "language:cat", "language:ces", "language:dan", "language:deu"]}
{"id": "hf-model:autogluon/chronos-2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "autogluon/chronos-2", "date": "2025-10-06", "createdAt": "2025-10-06", "sourceUpdatedAt": "2025-10-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 14253867 downloads and tags: chronos-forecasting, safetensors, t5, time series.", "popularity": {"value": 14253867, "label": "downloads"}, "url": "https://huggingface.co/autogluon/chronos-2", "tags": ["chronos-forecasting", "forecasting", "foundation models", "llm", "pretrained models", "safetensors", "t5", "time series"]}
{"id": "hf-dataset:nick007x/arxiv-papers", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nick007x/arxiv-papers", "date": "2026-04-01", "createdAt": "2025-09-29", "sourceUpdatedAt": "2026-04-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 890540 downloads.", "popularity": {"value": 890540, "label": "downloads"}, "url": "https://huggingface.co/datasets/nick007x/arxiv-papers", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:document", "modality:text"]}
{"id": "github:iptag/jimeng-api", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "iptag/jimeng-api", "date": "2026-03-02", "createdAt": "2025-09-28", "sourceUpdatedAt": "2026-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Reverse-engineered the official API for Jimeng/Dreamina’s text-to-image and image-to-image features. Drew inspiration from several experts’ projects and made some tweaks, which significantly improved stability.", "popularity": {"value": 981, "label": "stars"}, "url": "https://github.com/iptag/jimeng-api", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:hf-internal-testing/hf_hub_cache", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/hf_hub_cache", "date": "2025-09-26", "createdAt": "2025-09-26", "sourceUpdatedAt": "2025-09-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 132133 downloads.", "popularity": {"value": 132133, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/hf_hub_cache", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:openai/gdpval", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "openai/gdpval", "date": "2026-02-10", "createdAt": "2025-09-25", "sourceUpdatedAt": "2026-02-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 64226 downloads.", "popularity": {"value": 64226, "label": "downloads"}, "url": "https://huggingface.co/datasets/openai/gdpval", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-model:tencent/HunyuanImage-3.0", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "tencent/HunyuanImage-3.0", "date": "2025-09-25", "createdAt": "2025-09-25", "sourceUpdatedAt": "2025-09-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1097295 downloads and tags: transformers, safetensors, hunyuan_image_3_moe, text-generation.", "popularity": {"value": 1097295, "label": "downloads"}, "url": "https://huggingface.co/tencent/HunyuanImage-3.0", "tags": ["arxiv:2509.23951", "custom_code", "hunyuan_image_3_moe", "image-generation", "license:other", "safetensors", "text-generation", "text-to-image"]}
{"id": "hf-model:Qwen/Qwen3Guard-Gen-0.6B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3Guard-Gen-0.6B", "date": "2025-09-23", "createdAt": "2025-09-23", "sourceUpdatedAt": "2025-09-23", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face model with 2967484 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 2967484, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B", "tags": ["arxiv:2510.14276", "base_model:finetune:qwen/qwen3-0.6b", "base_model:qwen/qwen3-0.6b", "conversational", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "hf-dataset:boltzgen/inference-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "boltzgen/inference-data", "date": "2025-09-23", "createdAt": "2025-09-22", "sourceUpdatedAt": "2025-09-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 137375 downloads.", "popularity": {"value": 137375, "label": "downloads"}, "url": "https://huggingface.co/datasets/boltzgen/inference-data", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:p-e-w/heretic", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "p-e-w/heretic", "date": "2026-06-03", "createdAt": "2025-09-21", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fully automatic censorship removal for language models", "popularity": {"value": 23439, "label": "stars"}, "url": "https://github.com/p-e-w/heretic", "tags": ["llm", "tools"]}
{"id": "hf-dataset:buithutrang2004/buithutrang2004", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "buithutrang2004/buithutrang2004", "date": "2026-05-31", "createdAt": "2025-09-20", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47602 downloads.", "popularity": {"value": 47602, "label": "downloads"}, "url": "https://huggingface.co/datasets/buithutrang2004/buithutrang2004", "tags": ["datasets", "region:us"]}
{"id": "hf-model:John6666/one-obsession-17-red-sdxl", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "John6666/one-obsession-17-red-sdxl", "date": "2025-09-18", "createdAt": "2025-09-18", "sourceUpdatedAt": "2025-09-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 300886 downloads and tags: diffusers, safetensors, text-to-image, stable-diffusion.", "popularity": {"value": 300886, "label": "downloads"}, "url": "https://huggingface.co/John6666/one-obsession-17-red-sdxl", "tags": ["anime", "diffusers", "girls", "image-generation", "not-for-all-audiences", "safetensors", "stable-diffusion", "stable-diffusion-xl"]}
{"id": "github:verygoodplugins/automem", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "verygoodplugins/automem", "date": "2026-05-23", "createdAt": "2025-09-16", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AutoMem is a graph-vector memory service that gives AI assistants durable, relational memory:", "popularity": {"value": 745, "label": "stars"}, "url": "https://github.com/verygoodplugins/automem", "tags": ["tools", "vector-database"]}
{"id": "hf-dataset:hoangthuyvy2004/hoangthuyvy2004", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hoangthuyvy2004/hoangthuyvy2004", "date": "2026-06-03", "createdAt": "2025-09-14", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51774 downloads.", "popularity": {"value": 51774, "label": "downloads"}, "url": "https://huggingface.co/datasets/hoangthuyvy2004/hoangthuyvy2004", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:InternRobotics/OmniWorld", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "InternRobotics/OmniWorld", "date": "2026-04-17", "createdAt": "2025-09-14", "sourceUpdatedAt": "2026-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62534 downloads.", "popularity": {"value": 62534, "label": "downloads"}, "url": "https://huggingface.co/datasets/InternRobotics/OmniWorld", "tags": ["arxiv:2509.12201", "datasets", "format:webdataset", "language:en", "library:datasets", "library:mlcroissant", "library:webdataset", "license:cc-by-nc-sa-4.0"]}
{"id": "hf-dataset:mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M", "date": "2025-11-24", "createdAt": "2025-09-14", "sourceUpdatedAt": "2025-11-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 142291 downloads.", "popularity": {"value": 142291, "label": "downloads"}, "url": "https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M", "tags": ["arxiv:2509.23661", "datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:apache-2.0"]}
{"id": "github:vllm-project/vllm-omni", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vllm-project/vllm-omni", "date": "2026-06-04", "createdAt": "2025-09-11", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A framework for efficient model inference with omni-modality models", "popularity": {"value": 4914, "label": "stars"}, "url": "https://github.com/vllm-project/vllm-omni", "tags": ["inference"]}
{"id": "github:facebookresearch/meta-agents-research-environments", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "facebookresearch/meta-agents-research-environments", "date": "2026-06-04", "createdAt": "2025-09-11", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new informatio...", "popularity": {"value": 508, "label": "stars"}, "url": "https://github.com/facebookresearch/meta-agents-research-environments", "tags": ["agents", "evaluation"]}
{"id": "github:horizonwind2004/reconstruction-alignment", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HorizonWind2004/reconstruction-alignment", "date": "2026-05-23", "createdAt": "2025-09-10", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[ICLR 2026] Official repo of paper \"Reconstruction Alignment Improves Unified Multimodal Models\". Unlocking the Massive Zero-shot Potential in Unified Multimodal Models through Self-supervised Learning.", "popularity": {"value": 403, "label": "stars"}, "url": "https://github.com/HorizonWind2004/reconstruction-alignment", "tags": ["text-to-image", "tools"]}
{"id": "github:hunyuan-promptenhancer/promptenhancer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Hunyuan-PromptEnhancer/PromptEnhancer", "date": "2026-05-18", "createdAt": "2025-09-09", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[CVPR 2026] PromptEnhancer is a prompt-rewriting tool, refining prompts into clearer, structured versions for better image generation.", "popularity": {"value": 3697, "label": "stars"}, "url": "https://github.com/Hunyuan-PromptEnhancer/PromptEnhancer", "tags": ["developer-tools", "text-to-image"]}
{"id": "hf-dataset:meta-agents-research-environments/gaia2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "meta-agents-research-environments/gaia2", "date": "2025-09-25", "createdAt": "2025-09-09", "sourceUpdatedAt": "2025-09-25", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 49565 downloads.", "popularity": {"value": 49565, "label": "downloads"}, "url": "https://huggingface.co/datasets/meta-agents-research-environments/gaia2", "tags": ["adaptability", "agent-evaluation", "ai-assistant", "ambiguity", "annotations_creators:expert-generated", "arxiv:2509.17158", "benchmark", "datasets"]}
{"id": "github:oxbshw/llm-agents-ecosystem-handbook", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "oxbshw/LLM-Agents-Ecosystem-Handbook", "date": "2026-05-09", "createdAt": "2025-09-08", "sourceUpdatedAt": "2026-05-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.", "popularity": {"value": 528, "label": "stars"}, "url": "https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:mvp-lab/LLaVA-OneVision-1.5-Instruct-Data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mvp-lab/LLaVA-OneVision-1.5-Instruct-Data", "date": "2025-11-21", "createdAt": "2025-09-08", "sourceUpdatedAt": "2025-11-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 92713 downloads.", "popularity": {"value": 92713, "label": "downloads"}, "url": "https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Instruct-Data", "tags": ["arxiv:2509.23661", "dataset-collection", "datasets", "image-captioning", "instruction-tuning", "language:en", "large-language-model", "license:apache-2.0"]}
{"id": "github:datawhalechina/hello-agents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "datawhalechina/hello-agents", "date": "2026-06-03", "createdAt": "2025-09-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程", "popularity": {"value": 56099, "label": "stars"}, "url": "https://github.com/datawhalechina/hello-agents", "tags": ["agents", "llm"]}
{"id": "hf-dataset:Hostip51/Js", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Hostip51/Js", "date": "2026-06-03", "createdAt": "2025-09-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54438 downloads.", "popularity": {"value": 54438, "label": "downloads"}, "url": "https://huggingface.co/datasets/Hostip51/Js", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:HuggingFaceFW/finepdfs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/finepdfs", "date": "2026-04-03", "createdAt": "2025-09-05", "sourceUpdatedAt": "2026-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63355 downloads.", "popularity": {"value": 63355, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/finepdfs", "tags": ["arxiv:2109.07445", "arxiv:2506.18421", "datasets", "format:parquet", "language:aai", "language:aak", "language:aau", "language:aaz"]}
{"id": "github:angular/web-codegen-scorer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "angular/web-codegen-scorer", "date": "2026-05-05", "createdAt": "2025-09-04", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Web Codegen Scorer is a tool for evaluating the quality of web code generated by LLMs.", "popularity": {"value": 748, "label": "stars"}, "url": "https://github.com/angular/web-codegen-scorer", "tags": ["evaluation"]}
{"id": "github:tencent-hunyuan/hunyuanimage-2.1", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Tencent-Hunyuan/HunyuanImage-2.1", "date": "2025-10-14", "createdAt": "2025-09-04", "sourceUpdatedAt": "2025-10-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "HunyuanImage-2.1: An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation​", "popularity": {"value": 673, "label": "stars"}, "url": "https://github.com/Tencent-Hunyuan/HunyuanImage-2.1", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:smol-course/images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "smol-course/images", "date": "2025-09-24", "createdAt": "2025-09-02", "sourceUpdatedAt": "2025-09-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 99012 downloads.", "popularity": {"value": 99012, "label": "downloads"}, "url": "https://huggingface.co/datasets/smol-course/images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "github:thedotmack/claude-mem", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "thedotmack/claude-mem", "date": "2026-06-03", "createdAt": "2025-08-31", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Persistent Context Across Sessions for Every Agent –  Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenC...", "popularity": {"value": 80499, "label": "stars"}, "url": "https://github.com/thedotmack/claude-mem", "tags": ["agents", "rag"]}
{"id": "github:markfulton/nanobananaeditor", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "markfulton/NanoBananaEditor", "date": "2026-05-14", "createdAt": "2025-08-31", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The most advanced Nano Banana image generator and editor application. Your central hub for AI image generation and revisions. Intuitive UI features reference images, editing with image masks, version history, and more. Powered by Gemini 2.5 Flash images API.", "popularity": {"value": 685, "label": "stars"}, "url": "https://github.com/markfulton/NanoBananaEditor", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:ryanmarten/OpenThoughts-1k-sample", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ryanmarten/OpenThoughts-1k-sample", "date": "2025-08-31", "createdAt": "2025-08-30", "sourceUpdatedAt": "2025-08-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 764084 downloads.", "popularity": {"value": 764084, "label": "downloads"}, "url": "https://huggingface.co/datasets/ryanmarten/OpenThoughts-1k-sample", "tags": ["arxiv:2506.04178", "datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text"]}
{"id": "hf-dataset:epfml/FineWeb-HQ", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "epfml/FineWeb-HQ", "date": "2025-09-30", "createdAt": "2025-08-29", "sourceUpdatedAt": "2025-09-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 85694 downloads.", "popularity": {"value": 85694, "label": "downloads"}, "url": "https://huggingface.co/datasets/epfml/FineWeb-HQ", "tags": ["arxiv:2502.10361", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "github:frankbria/ralph-claude-code", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "frankbria/ralph-claude-code", "date": "2026-06-02", "createdAt": "2025-08-27", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Autonomous AI development loop for Claude Code with intelligent exit detection", "popularity": {"value": 9250, "label": "stars"}, "url": "https://github.com/frankbria/ralph-claude-code", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:ZahidYasinMittha/American-Sign-Language-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ZahidYasinMittha/American-Sign-Language-Dataset", "date": "2025-08-28", "createdAt": "2025-08-27", "sourceUpdatedAt": "2025-08-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 212316 downloads.", "popularity": {"value": 212316, "label": "downloads"}, "url": "https://huggingface.co/datasets/ZahidYasinMittha/American-Sign-Language-Dataset", "tags": ["american sign language", "asl", "datasets", "gesture recognition", "library:datasets", "library:mlcroissant", "license:mit", "modality:video"]}
{"id": "hf-dataset:ScaleAI/SWE-bench_Pro", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ScaleAI/SWE-bench_Pro", "date": "2026-02-23", "createdAt": "2025-08-26", "sourceUpdatedAt": "2026-02-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54957 downloads.", "popularity": {"value": 54957, "label": "downloads"}, "url": "https://huggingface.co/datasets/ScaleAI/SWE-bench_Pro", "tags": ["benchmark:eval-yaml", "benchmark:official", "datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "github:nvidia-nemo/gym", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NVIDIA-NeMo/Gym", "date": "2026-06-04", "createdAt": "2025-08-25", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Evaluate and improve models and agents using environments", "popularity": {"value": 943, "label": "stars"}, "url": "https://github.com/NVIDIA-NeMo/Gym", "tags": ["agents", "evaluation"]}
{"id": "hf-dataset:behavior-1k/2025-challenge-demos", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "behavior-1k/2025-challenge-demos", "date": "2025-12-02", "createdAt": "2025-08-22", "sourceUpdatedAt": "2025-12-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 122462 downloads.", "popularity": {"value": 122462, "label": "downloads"}, "url": "https://huggingface.co/datasets/behavior-1k/2025-challenge-demos", "tags": [".", "1", "2", "arxiv:2403.09227", "datasets", "doi:10.57967/hf/6394", "lerobot", "license:mit"]}
{"id": "hf-model:PaddlePaddle/en_PP-OCRv5_mobile_rec", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/en_PP-OCRv5_mobile_rec", "date": "2025-08-21", "createdAt": "2025-08-21", "sourceUpdatedAt": "2025-08-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 353229 downloads and tags: PaddleOCR, OCR, PaddlePaddle, textline_recognition.", "popularity": {"value": 353229, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/en_PP-OCRv5_mobile_rec", "tags": ["en", "image-to-text", "license:apache-2.0", "multimodal", "ocr", "paddleocr", "paddlepaddle", "region:us"]}
{"id": "hf-dataset:OpenSQZ/AutoMathText-V2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "OpenSQZ/AutoMathText-V2", "date": "2026-04-02", "createdAt": "2025-08-20", "sourceUpdatedAt": "2026-04-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 199702 downloads.", "popularity": {"value": 199702, "label": "downloads"}, "url": "https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2", "tags": ["arxiv:2402.07625", "datasets", "finetuning", "language:en", "language:zh", "llm", "math", "midtraining"]}
{"id": "hf-dataset:pwc-archive/evaluation-tables", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "pwc-archive/evaluation-tables", "date": "2025-09-13", "createdAt": "2025-08-18", "sourceUpdatedAt": "2025-09-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 163965 downloads.", "popularity": {"value": 163965, "label": "downloads"}, "url": "https://huggingface.co/datasets/pwc-archive/evaluation-tables", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:cc-by-sa-4.0", "modality:text"]}
{"id": "hf-dataset:phamha2001/phamha2001", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "phamha2001/phamha2001", "date": "2026-06-03", "createdAt": "2025-08-14", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 68005 downloads.", "popularity": {"value": 68005, "label": "downloads"}, "url": "https://huggingface.co/datasets/phamha2001/phamha2001", "tags": ["datasets", "region:us"]}
{"id": "github:best-of-ai/best-of-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "best-of-ai/best-of-ai", "date": "2026-06-01", "createdAt": "2025-08-14", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of best ai tools", "popularity": {"value": 615, "label": "stars"}, "url": "https://github.com/best-of-ai/best-of-ai", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:nvidia/Nemotron-CC-Math-v1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/Nemotron-CC-Math-v1", "date": "2025-12-23", "createdAt": "2025-08-14", "sourceUpdatedAt": "2025-12-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 87563 downloads.", "popularity": {"value": 87563, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/Nemotron-CC-Math-v1", "tags": ["arxiv:2410.12881", "arxiv:2508.14444", "arxiv:2508.15096", "datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "github:jd-opensource/xllm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jd-opensource/xllm", "date": "2026-06-04", "createdAt": "2025-08-12", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A high-performance inference engine for LLM, VLM, DiT and REC models, optimized for diverse AI accelerators.", "popularity": {"value": 1317, "label": "stars"}, "url": "https://github.com/jd-opensource/xllm", "tags": ["inference"]}
{"id": "github:hackerai-tech/hackerai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "hackerai-tech/hackerai", "date": "2026-06-03", "createdAt": "2025-08-09", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Find and fix vulnerabilities by chatting with AI", "popularity": {"value": 574, "label": "stars"}, "url": "https://github.com/hackerai-tech/hackerai", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:vibheksoni/stealth-browser-mcp", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vibheksoni/stealth-browser-mcp", "date": "2026-05-24", "createdAt": "2025-08-09", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The only browser automation that bypasses anti-bot systems. AI writes network hooks, clones UIs pixel-perfect via simple chat.", "popularity": {"value": 673, "label": "stars"}, "url": "https://github.com/vibheksoni/stealth-browser-mcp", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-model:lightx2v/Qwen-Image-Lightning", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "lightx2v/Qwen-Image-Lightning", "date": "2025-08-09", "createdAt": "2025-08-09", "sourceUpdatedAt": "2025-08-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 396352 downloads and tags: diffusers, Qwen-Image, distillation, LoRA.", "popularity": {"value": 396352, "label": "downloads"}, "url": "https://huggingface.co/lightx2v/Qwen-Image-Lightning", "tags": ["diffusers", "distillation", "en", "image-generation", "lora", "qwen-image", "text-to-image", "zh"]}
{"id": "github:sirmalloc/ccstatusline", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "sirmalloc/ccstatusline", "date": "2026-06-02", "createdAt": "2025-08-08", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🚀 Beautiful highly customizable statusline for Claude Code CLI with powerline support, themes, and more.", "popularity": {"value": 10183, "label": "stars"}, "url": "https://github.com/sirmalloc/ccstatusline", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:iofficeai/aionui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "iOfficeAI/AionUi", "date": "2026-06-04", "createdAt": "2025-08-07", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Free, local, open-source 24/7 Cowork app for OpenClaw, Hermes Agent, Claude Code, Codex, OpenCode, Gemini CLI and 20+ more CLI | Customize your assistants | Star if you like it!", "popularity": {"value": 27526, "label": "stars"}, "url": "https://github.com/iOfficeAI/AionUi", "tags": ["agents", "llm"]}
{"id": "github:usestrix/strix", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "usestrix/strix", "date": "2026-06-04", "createdAt": "2025-08-05", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source AI hackers to find and fix your app’s vulnerabilities.", "popularity": {"value": 25795, "label": "stars"}, "url": "https://github.com/usestrix/strix", "tags": ["llm", "tools"]}
{"id": "hf-model:google/gemma-3-270m", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "google/gemma-3-270m", "date": "2025-08-05", "createdAt": "2025-08-05", "sourceUpdatedAt": "2025-08-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 6846144 downloads and tags: transformers, safetensors, gemma3, gemma.", "popularity": {"value": 6846144, "label": "downloads"}, "url": "https://huggingface.co/google/gemma-3-270m", "tags": ["arxiv:1905.07830", "arxiv:2503.19786", "gemma", "gemma3", "google", "llm", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-4B-Instruct-2507", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-4B-Instruct-2507", "date": "2025-08-05", "createdAt": "2025-08-05", "sourceUpdatedAt": "2025-08-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5095792 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 5095792, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507", "tags": ["arxiv:2505.09388", "conversational", "eval-results", "license:apache-2.0", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "github:farion1231/cc-switch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "farion1231/cc-switch", "date": "2026-06-04", "createdAt": "2025-08-04", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Gemini CLI & Hermes Agent. Only official website: ccswitch.io", "popularity": {"value": 90729, "label": "stars"}, "url": "https://github.com/farion1231/cc-switch", "tags": ["agents", "ai-tools"]}
{"id": "github:inmve/free-ai-coding", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "inmve/free-ai-coding", "date": "2025-12-05", "createdAt": "2025-08-04", "sourceUpdatedAt": "2025-12-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI coding tools that give free Claude Opus/Sonnet, GPT-5, Gemini Pro, and other pro-grade models", "popularity": {"value": 734, "label": "stars"}, "url": "https://github.com/inmve/free-ai-coding", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:KAKA22/SpreadsheetBench", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "KAKA22/SpreadsheetBench", "date": "2025-12-03", "createdAt": "2025-08-04", "sourceUpdatedAt": "2025-12-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 179291 downloads.", "popularity": {"value": 179291, "label": "downloads"}, "url": "https://huggingface.co/datasets/KAKA22/SpreadsheetBench", "tags": ["arxiv:2406.14991", "datasets", "license:cc-by-sa-4.0", "region:us"]}
{"id": "hf-model:openai/gpt-oss-20b", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/gpt-oss-20b", "date": "2025-08-04", "createdAt": "2025-08-04", "sourceUpdatedAt": "2025-08-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 7877081 downloads and tags: transformers, safetensors, gpt_oss, text-generation.", "popularity": {"value": 7877081, "label": "downloads"}, "url": "https://huggingface.co/openai/gpt-oss-20b", "tags": ["arxiv:2508.10925", "conversational", "gpt_oss", "license:apache-2.0", "llm", "safetensors", "text-generation", "transformers"]}
{"id": "hf-model:openai/gpt-oss-120b", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/gpt-oss-120b", "date": "2025-08-04", "createdAt": "2025-08-04", "sourceUpdatedAt": "2025-08-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4609374 downloads and tags: transformers, safetensors, gpt_oss, text-generation.", "popularity": {"value": 4609374, "label": "downloads"}, "url": "https://huggingface.co/openai/gpt-oss-120b", "tags": ["arxiv:2508.10925", "conversational", "gpt_oss", "license:apache-2.0", "llm", "safetensors", "text-generation", "transformers"]}
{"id": "github:ufomiao/zcf", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "UfoMiao/zcf", "date": "2026-06-03", "createdAt": "2025-07-30", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Zero-Config Code Flow for Claude code & Codex", "popularity": {"value": 6027, "label": "stars"}, "url": "https://github.com/UfoMiao/zcf", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:candylion/mapillary-vistas-v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "candylion/mapillary-vistas-v2", "date": "2025-07-30", "createdAt": "2025-07-30", "sourceUpdatedAt": "2025-07-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 89651 downloads.", "popularity": {"value": 89651, "label": "downloads"}, "url": "https://huggingface.co/datasets/candylion/mapillary-vistas-v2", "tags": ["datasets", "license:cc-by-nc-sa-4.0", "modality:image", "region:us"]}
{"id": "hf-dataset:fineinstructions/fineinstructions_nemotron", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fineinstructions/fineinstructions_nemotron", "date": "2026-01-30", "createdAt": "2025-07-29", "sourceUpdatedAt": "2026-01-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 292441 downloads.", "popularity": {"value": 292441, "label": "downloads"}, "url": "https://huggingface.co/datasets/fineinstructions/fineinstructions_nemotron", "tags": ["arxiv:2601.22146", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:HuggingFaceM4/FineVision", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceM4/FineVision", "date": "2025-10-21", "createdAt": "2025-07-28", "sourceUpdatedAt": "2025-10-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 163017 downloads.", "popularity": {"value": 163017, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceM4/FineVision", "tags": ["arxiv:2510.17269", "datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:image"]}
{"id": "github:memorilabs/memori", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MemoriLabs/Memori", "date": "2026-06-03", "createdAt": "2025-07-24", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.", "popularity": {"value": 15173, "label": "stars"}, "url": "https://github.com/MemoriLabs/Memori", "tags": ["agents", "rag"]}
{"id": "hf-dataset:Helsinki-NLP/fineweb-edu-translated", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Helsinki-NLP/fineweb-edu-translated", "date": "2026-04-22", "createdAt": "2025-07-24", "sourceUpdatedAt": "2026-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 156616 downloads.", "popularity": {"value": 156616, "label": "downloads"}, "url": "https://huggingface.co/datasets/Helsinki-NLP/fineweb-edu-translated", "tags": ["datasets", "format:parquet", "language:bos", "language:bul", "language:cat", "language:ces", "language:dan", "language:deu"]}
{"id": "hf-dataset:InternRobotics/InternData-N1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "InternRobotics/InternData-N1", "date": "2026-02-06", "createdAt": "2025-07-24", "sourceUpdatedAt": "2026-02-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67647 downloads.", "popularity": {"value": 67647, "label": "downloads"}, "url": "https://huggingface.co/datasets/InternRobotics/InternData-N1", "tags": ["datasets", "language:en", "license:cc-by-sa-4.0", "navigation", "region:us", "size_categories:n>1t", "task_categories:robotics"]}
{"id": "hf-dataset:yunfanlu/RGB-Event-ISP-Dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "yunfanlu/RGB-Event-ISP-Dataset", "date": "2026-04-27", "createdAt": "2025-07-23", "sourceUpdatedAt": "2026-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49656 downloads.", "popularity": {"value": 49656, "label": "downloads"}, "url": "https://huggingface.co/datasets/yunfanlu/RGB-Event-ISP-Dataset", "tags": ["datasets", "event", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:cc-by-nc-sa-4.0", "modality:image", "region:us"]}
{"id": "github:nousresearch/hermes-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NousResearch/hermes-agent", "date": "2026-06-04", "createdAt": "2025-07-22", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The agent that grows with you", "popularity": {"value": 179342, "label": "stars"}, "url": "https://github.com/NousResearch/hermes-agent", "tags": ["agents", "llm"]}
{"id": "github:tencent/weknora", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Tencent/WeKnora", "date": "2026-06-03", "createdAt": "2025-07-22", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.", "popularity": {"value": 15967, "label": "stars"}, "url": "https://github.com/Tencent/WeKnora", "tags": ["agents", "rag"]}
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{"id": "hf-dataset:HPLT/DocHPLT", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HPLT/DocHPLT", "date": "2026-01-13", "createdAt": "2025-07-09", "sourceUpdatedAt": "2026-01-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66316 downloads.", "popularity": {"value": 66316, "label": "downloads"}, "url": "https://huggingface.co/datasets/HPLT/DocHPLT", "tags": ["arxiv:2508.13079", "datasets", "format:parquet", "language:af", "language:ar", "language:az", "language:be", "language:bg"]}
{"id": "github:liyupi/ai-code-helper", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "liyupi/ai-code-helper", "date": "2025-07-10", "createdAt": "2025-07-09", "sourceUpdatedAt": "2025-07-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "2025 年 AI 编程助手实战项目（作者：程序员鱼皮），基于 Spring Boot 3.5 + Java 21 + LangChain4j + AI 构建智能编程学习与求职辅导机器人，覆盖 AI 大模型接入、LangChain4j 核心特性、流式对话、Prompt 工程、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、Web 爬虫、安全防护、Vue.js 前端开发、SSE 服务端推送等企业级 AI 应用开发技术。帮助开发者掌握 AI 时代必备技能，熟悉 LangC...", "popularity": {"value": 674, "label": "stars"}, "url": "https://github.com/liyupi/ai-code-helper", "tags": ["rag", "vector-database"]}
{"id": "github:zhouxiaoka/autoclip", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zhouxiaoka/autoclip", "date": "2026-06-03", "createdAt": "2025-07-08", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AutoClip : AI-powered video clipping and highlight generation · 一款智能高光提取与剪辑的二创工具", "popularity": {"value": 5553, "label": "stars"}, "url": "https://github.com/zhouxiaoka/autoclip", "tags": ["ai-tools", "video-tools"]}
{"id": "github:agentscope-ai/openjudge", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "agentscope-ai/OpenJudge", "date": "2026-05-29", "createdAt": "2025-07-08", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenJudge: A Unified Framework for Holistic Evaluation and Quality Rewards", "popularity": {"value": 635, "label": "stars"}, "url": "https://github.com/agentscope-ai/OpenJudge", "tags": ["agents", "evaluation"]}
{"id": "github:google/langextract", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "google/langextract", "date": "2026-05-21", "createdAt": "2025-07-08", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.", "popularity": {"value": 36797, "label": "stars"}, "url": "https://github.com/google/langextract", "tags": ["llm", "tools"]}
{"id": "github:memtensor/memos", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MemTensor/MemOS", "date": "2026-06-04", "createdAt": "2025-07-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings", "popularity": {"value": 9520, "label": "stars"}, "url": "https://github.com/MemTensor/MemOS", "tags": ["agents", "rag"]}
{"id": "hf-dataset:klieret/swe-bench-dummy-test-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "klieret/swe-bench-dummy-test-dataset", "date": "2025-07-01", "createdAt": "2025-07-01", "sourceUpdatedAt": "2025-07-01", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47241 downloads.", "popularity": {"value": 47241, "label": "downloads"}, "url": "https://huggingface.co/datasets/klieret/swe-bench-dummy-test-dataset", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit", "modality:text"]}
{"id": "github:shareai-lab/learn-claude-code", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "shareAI-lab/learn-claude-code", "date": "2026-06-04", "createdAt": "2025-06-29", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Bash is all you need -  A nano claude code–like 「agent harness」, built from 0 to 1", "popularity": {"value": 64544, "label": "stars"}, "url": "https://github.com/shareAI-lab/learn-claude-code", "tags": ["agents", "llm"]}
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{"id": "github:swe-agent/mini-swe-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SWE-agent/mini-swe-agent", "date": "2026-06-03", "createdAt": "2025-06-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!", "popularity": {"value": 4868, "label": "stars"}, "url": "https://github.com/SWE-agent/mini-swe-agent", "tags": ["agents", "ai-agent"]}
{"id": "github:ai-for-developers/awesome-ai-coding-tools", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ai-for-developers/awesome-ai-coding-tools", "date": "2026-04-25", "createdAt": "2025-06-27", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of AI-powered coding tools", "popularity": {"value": 1761, "label": "stars"}, "url": "https://github.com/ai-for-developers/awesome-ai-coding-tools", "tags": ["ai-tools", "developer-tools"]}
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{"id": "github:haohao-end/openagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Haohao-end/openagent", "date": "2026-05-29", "createdAt": "2025-06-20", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Agent Development Platform - Supports multiple models (OpenAI/DeepSeek/Wenxin/Tongyi), knowledge base management, workflow automation, and enterprise-grade security. Built with Flask + Vue3 + LangChain, featuring one-click Docker deployment.", "popularity": {"value": 813, "label": "stars"}, "url": "https://github.com/Haohao-end/openagent", "tags": ["agents", "llmops"]}
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{"id": "github:oxylabs/oxylabs-ai-studio-py", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "oxylabs/oxylabs-ai-studio-py", "date": "2025-12-04", "createdAt": "2025-06-17", "sourceUpdatedAt": "2025-12-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Structured data gathering from any website using AI-powered scraper, crawler, and browser automation. Scraping and crawling with natural language prompts. Equip your LLM agents with fresh data. AI Studio python SDK for intelligent web data gathering.", "popularity": {"value": 2949, "label": "stars"}, "url": "https://github.com/oxylabs/oxylabs-ai-studio-py", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:EssentialAI/essential-web-v1.0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "EssentialAI/essential-web-v1.0", "date": "2025-10-02", "createdAt": "2025-06-17", "sourceUpdatedAt": "2025-10-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 269581 downloads.", "popularity": {"value": 269581, "label": "downloads"}, "url": "https://huggingface.co/datasets/EssentialAI/essential-web-v1.0", "tags": ["arxiv:2506.14111", "datasets", "license:odc-by", "region:us", "size_categories:10b<n<100b"]}
{"id": "github:nirdiamant/agents-towards-production", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NirDiamant/agents-towards-production", "date": "2026-06-03", "createdAt": "2025-06-16", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.", "popularity": {"value": 20605, "label": "stars"}, "url": "https://github.com/NirDiamant/agents-towards-production", "tags": ["agents", "rag"]}
{"id": "hf-dataset:world-igr-plum/regions", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "world-igr-plum/regions", "date": "2025-06-17", "createdAt": "2025-06-16", "sourceUpdatedAt": "2025-06-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 397784 downloads.", "popularity": {"value": 397784, "label": "downloads"}, "url": "https://huggingface.co/datasets/world-igr-plum/regions", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:qdhenry/claude-command-suite", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "qdhenry/Claude-Command-Suite", "date": "2026-03-01", "createdAt": "2025-06-13", "sourceUpdatedAt": "2026-03-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Professional slash commands for Claude Code that provide   structured workflows for software development tasks including   code review, feature creation, security auditing, and architectural analysis.", "popularity": {"value": 1275, "label": "stars"}, "url": "https://github.com/qdhenry/Claude-Command-Suite", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-model:PaddlePaddle/PP-LCNet_x1_0_textline_ori", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/PP-LCNet_x1_0_textline_ori", "date": "2025-06-12", "createdAt": "2025-06-12", "sourceUpdatedAt": "2025-06-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 252490 downloads and tags: PaddleOCR, OCR, PaddlePaddle, textline_orientation_classification.", "popularity": {"value": 252490, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/PP-LCNet_x1_0_textline_ori", "tags": ["en", "image-to-text", "license:apache-2.0", "multimodal", "ocr", "paddleocr", "paddlepaddle", "textline_orientation_classification"]}
{"id": "github:startrail-org/leann", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "StarTrail-org/LEANN", "date": "2026-06-03", "createdAt": "2025-06-09", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.", "popularity": {"value": 11860, "label": "stars"}, "url": "https://github.com/StarTrail-org/LEANN", "tags": ["rag"]}
{"id": "github:geeeekexplorer/nano-vllm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "GeeeekExplorer/nano-vllm", "date": "2026-04-26", "createdAt": "2025-06-09", "sourceUpdatedAt": "2026-04-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Nano vLLM", "popularity": {"value": 13835, "label": "stars"}, "url": "https://github.com/GeeeekExplorer/nano-vllm", "tags": ["inference"]}
{"id": "github:smythos/sre", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SmythOS/sre", "date": "2026-04-03", "createdAt": "2025-06-07", "sourceUpdatedAt": "2026-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime for agentic AI. Secure, modular, and production-ready, it lets developers build, run, and manage intelligent agents across local, cloud, and edge environments.", "popularity": {"value": 1272, "label": "stars"}, "url": "https://github.com/SmythOS/sre", "tags": ["agents", "llmops"]}
{"id": "github:purpleailab/decepticon", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "PurpleAILAB/Decepticon", "date": "2026-06-03", "createdAt": "2025-06-06", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Autonomous Hacking Agent for Red Team", "popularity": {"value": 4264, "label": "stars"}, "url": "https://github.com/PurpleAILAB/Decepticon", "tags": ["agents", "generative-ai"]}
{"id": "github:unicomai/wanwu", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "UnicomAI/wanwu", "date": "2026-06-01", "createdAt": "2025-06-06", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "China Unicom's Yuanjing Wanwu Agent Platform is an enterprise-grade, multi-tenant AI agent development platform. It helps users build applications such as intelligent agents, workflows, and rag, and also supports model management. The platform features a de...", "popularity": {"value": 2523, "label": "stars"}, "url": "https://github.com/UnicomAI/wanwu", "tags": ["agents", "ai-agent"]}
{"id": "github:zilliztech/claude-context", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zilliztech/claude-context", "date": "2026-05-22", "createdAt": "2025-06-06", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Code search MCP for Claude Code. Make entire codebase the context for any coding agent.", "popularity": {"value": 11700, "label": "stars"}, "url": "https://github.com/zilliztech/claude-context", "tags": ["agents", "rag"]}
{"id": "hf-model:PaddlePaddle/UVDoc", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/UVDoc", "date": "2025-06-06", "createdAt": "2025-06-06", "sourceUpdatedAt": "2025-06-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 514393 downloads and tags: PaddleOCR, OCR, PaddlePaddle, doc_img_unwarping.", "popularity": {"value": 514393, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/UVDoc", "tags": ["doc_img_unwarping", "en", "image-to-text", "license:apache-2.0", "multimodal", "ocr", "paddleocr", "paddlepaddle"]}
{"id": "hf-model:PaddlePaddle/PP-LCNet_x1_0_doc_ori", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/PP-LCNet_x1_0_doc_ori", "date": "2025-06-06", "createdAt": "2025-06-06", "sourceUpdatedAt": "2025-06-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 447553 downloads and tags: PaddleOCR, OCR, PaddlePaddle, doc_img_orientation_classification.", "popularity": {"value": 447553, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/PP-LCNet_x1_0_doc_ori", "tags": ["doc_img_orientation_classification", "en", "image-to-text", "license:apache-2.0", "multimodal", "ocr", "paddleocr", "paddlepaddle"]}
{"id": "hf-dataset:jxcai-scale/hle-public-questions", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jxcai-scale/hle-public-questions", "date": "2025-06-06", "createdAt": "2025-06-06", "sourceUpdatedAt": "2025-06-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 97999 downloads.", "popularity": {"value": 97999, "label": "downloads"}, "url": "https://huggingface.co/datasets/jxcai-scale/hle-public-questions", "tags": ["datasets", "format:csv", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:bgauryy/octocode", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bgauryy/octocode", "date": "2026-06-03", "createdAt": "2025-06-05", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "MCP server for semantic code research and context generation on real-time using LLM patterns | Search naturally across public & private repos based on your permissions | Transform any accessible codebase/s into AI-optimized knowledge on simple and complex f...", "popularity": {"value": 854, "label": "stars"}, "url": "https://github.com/bgauryy/octocode", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:datawhalechina/all-in-rag", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "datawhalechina/all-in-rag", "date": "2026-05-23", "createdAt": "2025-06-05", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/", "popularity": {"value": 8223, "label": "stars"}, "url": "https://github.com/datawhalechina/all-in-rag", "tags": ["rag"]}
{"id": "github:onestardao/wfgy", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "onestardao/WFGY", "date": "2026-06-03", "createdAt": "2025-06-04", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.", "popularity": {"value": 1753, "label": "stars"}, "url": "https://github.com/onestardao/WFGY", "tags": ["agents", "evaluation"]}
{"id": "hf-model:PaddlePaddle/PP-OCRv5_server_det", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/PP-OCRv5_server_det", "date": "2025-06-04", "createdAt": "2025-06-04", "sourceUpdatedAt": "2025-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 639870 downloads and tags: PaddleOCR, OCR, PaddlePaddle, textline_detection.", "popularity": {"value": 639870, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/PP-OCRv5_server_det", "tags": ["arxiv:1212.1442", "en", "image-to-text", "multimodal", "ocr", "paddleocr", "paddlepaddle", "textline_detection"]}
{"id": "hf-model:PaddlePaddle/PP-OCRv5_server_rec", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "PaddlePaddle/PP-OCRv5_server_rec", "date": "2025-06-04", "createdAt": "2025-06-04", "sourceUpdatedAt": "2025-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 208167 downloads and tags: PaddleOCR, OCR, PaddlePaddle, textline_recognition.", "popularity": {"value": 208167, "label": "downloads"}, "url": "https://huggingface.co/PaddlePaddle/PP-OCRv5_server_rec", "tags": ["arxiv:1212.1442", "en", "image-to-text", "multimodal", "ocr", "paddleocr", "paddlepaddle", "textline_recognition"]}
{"id": "github:bytedance-seed/evalearn", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ByteDance-Seed/EvaLearn", "date": "2026-05-12", "createdAt": "2025-06-03", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "EvaLearn is a pioneering benchmark designed to evaluate large language models (LLMs) on their learning capability and efficiency in challenging tasks.", "popularity": {"value": 431, "label": "stars"}, "url": "https://github.com/ByteDance-Seed/EvaLearn", "tags": ["evaluation"]}
{"id": "hf-model:Qwen/Qwen3-Embedding-0.6B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-Embedding-0.6B", "date": "2025-06-03", "createdAt": "2025-06-03", "sourceUpdatedAt": "2025-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 8761583 downloads and tags: sentence-transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 8761583, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-Embedding-0.6B", "tags": ["embeddings", "feature-extraction", "qwen3", "safetensors", "sentence-similarity", "sentence-transformers", "text-embeddings-inference", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-Embedding-4B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-Embedding-4B", "date": "2025-06-03", "createdAt": "2025-06-03", "sourceUpdatedAt": "2025-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2787908 downloads and tags: sentence-transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 2787908, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-Embedding-4B", "tags": ["embeddings", "feature-extraction", "qwen3", "safetensors", "sentence-similarity", "sentence-transformers", "text-embeddings-inference", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-Embedding-8B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-Embedding-8B", "date": "2025-06-03", "createdAt": "2025-06-03", "sourceUpdatedAt": "2025-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1865371 downloads and tags: sentence-transformers, safetensors, transformers, sentence-similarity.", "popularity": {"value": 1865371, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-Embedding-8B", "tags": ["arxiv:2506.05176", "base_model:qwen/qwen3-8b-base", "embeddings", "feature-extraction", "safetensors", "sentence-similarity", "sentence-transformers", "text-embeddings-inference"]}
{"id": "hf-model:ibm-granite/granite-vision-3.3-2b", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "ibm-granite/granite-vision-3.3-2b", "date": "2025-06-03", "createdAt": "2025-06-03", "sourceUpdatedAt": "2025-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 146111 downloads and tags: safetensors, llava_next, image-to-text, arxiv:2502.09927.", "popularity": {"value": 146111, "label": "downloads"}, "url": "https://huggingface.co/ibm-granite/granite-vision-3.3-2b", "tags": ["arxiv:2502.09927", "image-to-text", "license:apache-2.0", "llava_next", "multimodal", "region:us", "safetensors"]}
{"id": "hf-dataset:chenhn02/MetaFold", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "chenhn02/MetaFold", "date": "2025-10-28", "createdAt": "2025-05-30", "sourceUpdatedAt": "2025-10-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67963 downloads.", "popularity": {"value": 67963, "label": "downloads"}, "url": "https://huggingface.co/datasets/chenhn02/MetaFold", "tags": ["arxiv:2308.09987", "arxiv:2503.08372", "datasets", "language:en", "license:cc-by-nc-nd-4.0", "mesh", "region:us", "size_categories:10b<n<100b"]}
{"id": "github:aidc-ai/ovis-u1", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AIDC-AI/Ovis-U1", "date": "2025-12-02", "createdAt": "2025-05-29", "sourceUpdatedAt": "2025-12-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An unified model that seamlessly integrates multimodal understanding, text-to-image generation, and image editing within a single powerful framework.", "popularity": {"value": 448, "label": "stars"}, "url": "https://github.com/AIDC-AI/Ovis-U1", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:deepseek-ai/DeepSeek-R1-0528", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "deepseek-ai/DeepSeek-R1-0528", "date": "2025-05-28", "createdAt": "2025-05-28", "sourceUpdatedAt": "2025-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5886162 downloads and tags: transformers, safetensors, deepseek_v3, text-generation.", "popularity": {"value": 5886162, "label": "downloads"}, "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1-0528", "tags": ["arxiv:2501.12948", "coding", "conversational", "custom_code", "deepseek_v3", "license:mit", "safetensors", "text-generation"]}
{"id": "github:memvid/memvid", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "memvid/memvid", "date": "2026-05-27", "createdAt": "2025-05-27", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.", "popularity": {"value": 15615, "label": "stars"}, "url": "https://github.com/memvid/memvid", "tags": ["agents", "rag"]}
{"id": "hf-dataset:xlangai/ubuntu_osworld_file_cache", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "xlangai/ubuntu_osworld_file_cache", "date": "2026-05-07", "createdAt": "2025-05-27", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1209517 downloads.", "popularity": {"value": 1209517, "label": "downloads"}, "url": "https://huggingface.co/datasets/xlangai/ubuntu_osworld_file_cache", "tags": ["arxiv:2404.07972", "datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:nvidia/PhysicalAI-Autonomous-Vehicles", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/PhysicalAI-Autonomous-Vehicles", "date": "2026-05-06", "createdAt": "2025-05-27", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 150164 downloads.", "popularity": {"value": 150164, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles", "tags": ["datasets", "license:other", "region:us"]}
{"id": "hf-dataset:a2015003713/military-aircraft-detection-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "a2015003713/military-aircraft-detection-dataset", "date": "2026-05-15", "createdAt": "2025-05-24", "sourceUpdatedAt": "2026-05-15", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47958 downloads.", "popularity": {"value": 47958, "label": "downloads"}, "url": "https://huggingface.co/datasets/a2015003713/military-aircraft-detection-dataset", "tags": ["datasets", "format:text", "library:datasets", "library:mlcroissant", "modality:image", "modality:text", "region:us", "size_categories:10k<n<100k"]}
{"id": "hf-dataset:daniilakk/nbchr_pdfs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "daniilakk/nbchr_pdfs", "date": "2025-05-25", "createdAt": "2025-05-24", "sourceUpdatedAt": "2025-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 393226 downloads.", "popularity": {"value": 393226, "label": "downloads"}, "url": "https://huggingface.co/datasets/daniilakk/nbchr_pdfs", "tags": ["datasets", "license:unknown", "modality:document", "region:us"]}
{"id": "github:mcpjam/inspector", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MCPJam/inspector", "date": "2026-06-04", "createdAt": "2025-05-23", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Testing and evaluation platform to chat, inspect, and debug MCP servers, MCP apps, and ChatGPT apps.", "popularity": {"value": 1985, "label": "stars"}, "url": "https://github.com/MCPJam/inspector", "tags": ["evaluation"]}
{"id": "hf-dataset:daixianjie/robocasa_mg_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "daixianjie/robocasa_mg_lerobot", "date": "2025-05-29", "createdAt": "2025-05-21", "sourceUpdatedAt": "2025-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 75189 downloads.", "popularity": {"value": 75189, "label": "downloads"}, "url": "https://huggingface.co/datasets/daixianjie/robocasa_mg_lerobot", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:worldbenchmark/IntuitivePhysics", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "worldbenchmark/IntuitivePhysics", "date": "2026-05-07", "createdAt": "2025-05-16", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 59202 downloads.", "popularity": {"value": 59202, "label": "downloads"}, "url": "https://huggingface.co/datasets/worldbenchmark/IntuitivePhysics", "tags": ["datasets", "format:imagefolder", "language:en", "library:datasets", "library:mlcroissant", "mlcroissant", "modality:image", "region:us"]}
{"id": "hf-dataset:rsi/PixelsPointsPolygons", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rsi/PixelsPointsPolygons", "date": "2025-12-08", "createdAt": "2025-05-15", "sourceUpdatedAt": "2025-12-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58166 downloads.", "popularity": {"value": 58166, "label": "downloads"}, "url": "https://huggingface.co/datasets/rsi/PixelsPointsPolygons", "tags": ["aerial", "als", "arxiv:2505.15379", "building", "datasets", "earth observation", "environement", "image"]}
{"id": "hf-dataset:sunblaze-ucb/cybergym", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sunblaze-ucb/cybergym", "date": "2025-05-15", "createdAt": "2025-05-14", "sourceUpdatedAt": "2025-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51811 downloads.", "popularity": {"value": 51811, "label": "downloads"}, "url": "https://huggingface.co/datasets/sunblaze-ucb/cybergym", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:ieasybooks-org/shamela-waqfeya-library", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ieasybooks-org/shamela-waqfeya-library", "date": "2025-05-14", "createdAt": "2025-05-14", "sourceUpdatedAt": "2025-05-14", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46493 downloads.", "popularity": {"value": 46493, "label": "downloads"}, "url": "https://huggingface.co/datasets/ieasybooks-org/shamela-waqfeya-library", "tags": ["datasets", "format:csv", "language:ar", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "github:opendataloader-project/opendataloader-pdf", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "opendataloader-project/opendataloader-pdf", "date": "2026-06-03", "createdAt": "2025-05-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.", "popularity": {"value": 23358, "label": "stars"}, "url": "https://github.com/opendataloader-project/opendataloader-pdf", "tags": ["rag"]}
{"id": "github:presenton/presenton", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "presenton/presenton", "date": "2026-06-03", "createdAt": "2025-05-10", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-Source AI Presentation Generator and API (Gamma, Beautiful AI, Decktopus Alternative)", "popularity": {"value": 7820, "label": "stars"}, "url": "https://github.com/presenton/presenton", "tags": ["agents", "ai-agent"]}
{"id": "github:ibm/mcp-context-forge", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "IBM/mcp-context-forge", "date": "2026-06-03", "createdAt": "2025-05-08", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.", "popularity": {"value": 3814, "label": "stars"}, "url": "https://github.com/IBM/mcp-context-forge", "tags": ["agents", "generative-ai"]}
{"id": "github:docmd-io/docmd", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "docmd-io/docmd", "date": "2026-05-31", "createdAt": "2025-05-08", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build production-ready documentation from Markdown in seconds. No React, no bloat, just content.", "popularity": {"value": 1750, "label": "stars"}, "url": "https://github.com/docmd-io/docmd", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:bytedance/deer-flow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bytedance/deer-flow", "date": "2026-06-03", "createdAt": "2025-05-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.", "popularity": {"value": 70400, "label": "stars"}, "url": "https://github.com/bytedance/deer-flow", "tags": ["agents", "llm"]}
{"id": "hf-dataset:TianxingChen/RoboTwin2.0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "TianxingChen/RoboTwin2.0", "date": "2025-12-17", "createdAt": "2025-05-07", "sourceUpdatedAt": "2025-12-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 68318 downloads.", "popularity": {"value": 68318, "label": "downloads"}, "url": "https://huggingface.co/datasets/TianxingChen/RoboTwin2.0", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:kossakovsky/n8n-install", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "kossakovsky/n8n-install", "date": "2026-05-17", "createdAt": "2025-05-05", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🚀 Self-hosted AI automation platform. Deploy n8n, Ollama, Flowise, RAG, Supabase & 30+ tools with one command. Auto HTTPS. Free Zapier/Make alternative.", "popularity": {"value": 880, "label": "stars"}, "url": "https://github.com/kossakovsky/n8n-install", "tags": ["ui-demo", "vector-database"]}
{"id": "hf-dataset:ieasybooks-org/prophet-mosque-library", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ieasybooks-org/prophet-mosque-library", "date": "2025-05-14", "createdAt": "2025-05-04", "sourceUpdatedAt": "2025-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 149914 downloads.", "popularity": {"value": 149914, "label": "downloads"}, "url": "https://huggingface.co/datasets/ieasybooks-org/prophet-mosque-library", "tags": ["datasets", "format:csv", "language:ar", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "github:asgeirtj/system_prompts_leaks", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "asgeirtj/system_prompts_leaks", "date": "2026-06-04", "createdAt": "2025-05-03", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Extracted system prompts from Anthropic - Opus 4.7, Opus 4.6, Sonnet 4.6. OpenAI - ChatGPT 5.5 Thinking, GPT 5.5 Instant, Codex. Google Gemini - 3.5 Flash, 3.1 Pro, 3 Flash, Antigravity. xAI - Grok. Github Copilot. Perplexity, and more. Updated regularly.", "popularity": {"value": 41217, "label": "stars"}, "url": "https://github.com/asgeirtj/system_prompts_leaks", "tags": ["llm", "tools"]}
{"id": "hf-dataset:Metanova/Submission-Archive", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Metanova/Submission-Archive", "date": "2026-06-04", "createdAt": "2025-05-02", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 102542 downloads.", "popularity": {"value": 102542, "label": "downloads"}, "url": "https://huggingface.co/datasets/Metanova/Submission-Archive", "tags": ["datasets", "region:us"]}
{"id": "github:jetbrains/koog", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "JetBrains/koog", "date": "2026-06-03", "createdAt": "2025-05-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expert...", "popularity": {"value": 4307, "label": "stars"}, "url": "https://github.com/JetBrains/koog", "tags": ["agents", "generative-ai"]}
{"id": "github:llm-d/llm-d", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "llm-d/llm-d", "date": "2026-06-03", "createdAt": "2025-04-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Achieve state of the art inference performance with modern accelerators on Kubernetes", "popularity": {"value": 3293, "label": "stars"}, "url": "https://github.com/llm-d/llm-d", "tags": ["inference"]}
{"id": "hf-dataset:SWE-bench/SWE-bench_Verified", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SWE-bench/SWE-bench_Verified", "date": "2026-02-27", "createdAt": "2025-04-29", "sourceUpdatedAt": "2026-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 75426 downloads.", "popularity": {"value": 75426, "label": "downloads"}, "url": "https://huggingface.co/datasets/SWE-bench/SWE-bench_Verified", "tags": ["benchmark:eval-yaml", "benchmark:official", "datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:SWE-bench/SWE-bench_Multilingual", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SWE-bench/SWE-bench_Multilingual", "date": "2025-08-26", "createdAt": "2025-04-29", "sourceUpdatedAt": "2025-08-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 598063 downloads.", "popularity": {"value": 598063, "label": "downloads"}, "url": "https://huggingface.co/datasets/SWE-bench/SWE-bench_Multilingual", "tags": ["datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "hf-dataset:idegen/csts", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "idegen/csts", "date": "2025-05-21", "createdAt": "2025-04-29", "sourceUpdatedAt": "2025-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 189876 downloads.", "popularity": {"value": 189876, "label": "downloads"}, "url": "https://huggingface.co/datasets/idegen/csts", "tags": ["arxiv:2505.14596", "benchmark", "changepoint-detection", "correlation-structure", "datasets", "doi:10.57967/hf/6689", "format:parquet", "library:dask"]}
{"id": "hf-model:hmellor/tiny-random-LlamaForCausalLM", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "hmellor/tiny-random-LlamaForCausalLM", "date": "2025-04-29", "createdAt": "2025-04-29", "sourceUpdatedAt": "2025-04-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4226053 downloads and tags: transformers, safetensors, llama, text-generation.", "popularity": {"value": 4226053, "label": "downloads"}, "url": "https://huggingface.co/hmellor/tiny-random-LlamaForCausalLM", "tags": ["arxiv:1910.09700", "conversational", "endpoints_compatible", "llama", "safetensors", "small-local", "text-generation", "text-generation-inference"]}
{"id": "github:sansan0/trendradar", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "sansan0/TrendRadar", "date": "2026-06-02", "createdAt": "2025-04-28", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 +  RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 +  AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉...", "popularity": {"value": 58789, "label": "stars"}, "url": "https://github.com/sansan0/TrendRadar", "tags": ["llm", "tools"]}
{"id": "hf-model:Qwen/Qwen3-0.6B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-0.6B", "date": "2025-04-27", "createdAt": "2025-04-27", "sourceUpdatedAt": "2025-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 21592454 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 21592454, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-0.6B", "tags": ["arxiv:2505.09388", "base_model:finetune:qwen/qwen3-0.6b-base", "base_model:qwen/qwen3-0.6b-base", "conversational", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-4B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-4B", "date": "2025-04-27", "createdAt": "2025-04-27", "sourceUpdatedAt": "2025-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 15649936 downloads and tags: transformers, safetensors, text-generation, arxiv:2309.00071.", "popularity": {"value": 15649936, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-4B", "tags": ["arxiv:2309.00071", "arxiv:2505.09388", "base_model:finetune:qwen/qwen3-4b-base", "base_model:qwen/qwen3-4b-base", "license:apache-2.0", "llm", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-8B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-8B", "date": "2025-04-27", "createdAt": "2025-04-27", "sourceUpdatedAt": "2025-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 12457282 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 12457282, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-8B", "tags": ["arxiv:2309.00071", "arxiv:2505.09388", "base_model:qwen/qwen3-8b-base", "conversational", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-32B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-32B", "date": "2025-04-27", "createdAt": "2025-04-27", "sourceUpdatedAt": "2025-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4660504 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 4660504, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-32B", "tags": ["arxiv:2309.00071", "arxiv:2505.09388", "conversational", "license:apache-2.0", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen3-1.7B", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen3-1.7B", "date": "2025-04-27", "createdAt": "2025-04-27", "sourceUpdatedAt": "2025-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4644195 downloads and tags: transformers, safetensors, qwen3, text-generation.", "popularity": {"value": 4644195, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen3-1.7B", "tags": ["arxiv:2505.09388", "base_model:finetune:qwen/qwen3-1.7b-base", "base_model:qwen/qwen3-1.7b-base", "conversational", "llm", "qwen3", "safetensors", "text-generation"]}
{"id": "hf-dataset:onnx-community/model-explorer", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "onnx-community/model-explorer", "date": "2025-04-30", "createdAt": "2025-04-25", "sourceUpdatedAt": "2025-04-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49387 downloads.", "popularity": {"value": 49387, "label": "downloads"}, "url": "https://huggingface.co/datasets/onnx-community/model-explorer", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-model:ResembleAI/chatterbox", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "ResembleAI/chatterbox", "date": "2025-04-24", "createdAt": "2025-04-24", "sourceUpdatedAt": "2025-04-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1869010 downloads and tags: chatterbox, text-to-speech, speech, speech-generation.", "popularity": {"value": 1869010, "label": "downloads"}, "url": "https://huggingface.co/ResembleAI/chatterbox", "tags": ["ar", "audio", "chatterbox", "da", "multilingual-tts", "speech", "speech-generation", "text-to-speech"]}
{"id": "hf-dataset:Felix92/docTR-resource-collection", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Felix92/docTR-resource-collection", "date": "2026-01-16", "createdAt": "2025-04-22", "sourceUpdatedAt": "2026-01-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 187293 downloads.", "popularity": {"value": 187293, "label": "downloads"}, "url": "https://huggingface.co/datasets/Felix92/docTR-resource-collection", "tags": ["datasets", "format:text", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:text", "region:us", "size_categories:1k<n<10k"]}
{"id": "github:liyupi/yu-ai-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "liyupi/yu-ai-agent", "date": "2026-01-07", "createdAt": "2025-04-22", "sourceUpdatedAt": "2026-01-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "编程导航 2025 年 AI 开发实战新项目，基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus，覆盖 AI 大模型接入、Spring AI 核心特性、Prompt 工程和优化、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、AI Agent 开发（Manas Java 实现）、Cursor AI 工具等核心知识。用一套教程将程序员必知必会的 AI 技术一网打尽，帮你成...", "popularity": {"value": 2350, "label": "stars"}, "url": "https://github.com/liyupi/yu-ai-agent", "tags": ["agents", "vector-database"]}
{"id": "hf-dataset:ieasybooks-org/waqfeya-library", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ieasybooks-org/waqfeya-library", "date": "2025-05-14", "createdAt": "2025-04-22", "sourceUpdatedAt": "2025-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56978 downloads.", "popularity": {"value": 56978, "label": "downloads"}, "url": "https://huggingface.co/datasets/ieasybooks-org/waqfeya-library", "tags": ["datasets", "format:csv", "language:ar", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "github:dataease/sqlbot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dataease/SQLBot", "date": "2026-06-04", "createdAt": "2025-04-21", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔥 基于大模型和 RAG 的智能问数系统，对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.", "popularity": {"value": 6188, "label": "stars"}, "url": "https://github.com/dataease/SQLBot", "tags": ["rag"]}
{"id": "github:langwatch/better-agents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "langwatch/better-agents", "date": "2026-06-03", "createdAt": "2025-04-19", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Standards for building agents, better", "popularity": {"value": 1526, "label": "stars"}, "url": "https://github.com/langwatch/better-agents", "tags": ["agents", "llmops"]}
{"id": "github:hesreallyhim/awesome-claude-code", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "hesreallyhim/awesome-claude-code", "date": "2026-04-27", "createdAt": "2025-04-19", "sourceUpdatedAt": "2026-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic", "popularity": {"value": 45627, "label": "stars"}, "url": "https://github.com/hesreallyhim/awesome-claude-code", "tags": ["agents", "llm"]}
{"id": "github:voltagent/voltagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "VoltAgent/voltagent", "date": "2026-06-03", "createdAt": "2025-04-16", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework", "popularity": {"value": 9344, "label": "stars"}, "url": "https://github.com/VoltAgent/voltagent", "tags": ["agents", "rag"]}
{"id": "hf-model:pyannote/speaker-diarization-community-1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "pyannote/speaker-diarization-community-1", "date": "2025-04-15", "createdAt": "2025-04-15", "sourceUpdatedAt": "2025-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2781484 downloads and tags: pyannote-audio, pyannote, pyannote-audio-pipeline, audio.", "popularity": {"value": 2781484, "label": "downloads"}, "url": "https://huggingface.co/pyannote/speaker-diarization-community-1", "tags": ["audio", "pyannote", "pyannote-audio", "pyannote-audio-pipeline", "speaker", "speaker-diarization", "speech", "voice"]}
{"id": "hf-dataset:jackkuo/arXiv-metadata-oai-snapshot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jackkuo/arXiv-metadata-oai-snapshot", "date": "2025-04-14", "createdAt": "2025-04-14", "sourceUpdatedAt": "2025-04-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 153012 downloads.", "popularity": {"value": 153012, "label": "downloads"}, "url": "https://huggingface.co/datasets/jackkuo/arXiv-metadata-oai-snapshot", "tags": ["biology", "chemistry", "datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "github:glitternetwork/pinme", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "glitternetwork/pinme", "date": "2026-06-03", "createdAt": "2025-04-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Deploy Your Frontend in a Single Command. Claude Code Skills supported.", "popularity": {"value": 3609, "label": "stars"}, "url": "https://github.com/glitternetwork/pinme", "tags": ["ai-tools", "developer-tools"]}
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{"id": "hf-dataset:liamstone707/CORAAL", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "liamstone707/CORAAL", "date": "2025-04-12", "createdAt": "2025-04-12", "sourceUpdatedAt": "2025-04-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56832 downloads.", "popularity": {"value": 56832, "label": "downloads"}, "url": "https://huggingface.co/datasets/liamstone707/CORAAL", "tags": ["aae", "aal", "aave", "black english", "datasets", "ebonics", "language:en", "license:cc-by-nc-sa-4.0"]}
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{"id": "hf-dataset:RoboVerseOrg/roboverse_data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "RoboVerseOrg/roboverse_data", "date": "2026-06-03", "createdAt": "2025-04-11", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 74462 downloads.", "popularity": {"value": 74462, "label": "downloads"}, "url": "https://huggingface.co/datasets/RoboVerseOrg/roboverse_data", "tags": ["arxiv:2504.18904", "datasets", "license:apache-2.0", "region:us", "task_categories:robotics"]}
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{"id": "hf-dataset:chonkie-ai/recipes", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "chonkie-ai/recipes", "date": "2025-10-07", "createdAt": "2025-04-08", "sourceUpdatedAt": "2025-10-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51651 downloads.", "popularity": {"value": 51651, "label": "downloads"}, "url": "https://huggingface.co/datasets/chonkie-ai/recipes", "tags": ["datasets", "format:json", "library:dask", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:text", "region:us"]}
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{"id": "hf-dataset:VLM2Vec/MSR-VTT", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "VLM2Vec/MSR-VTT", "date": "2025-08-03", "createdAt": "2025-04-07", "sourceUpdatedAt": "2025-08-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 178958 downloads.", "popularity": {"value": 178958, "label": "downloads"}, "url": "https://huggingface.co/datasets/VLM2Vec/MSR-VTT", "tags": ["datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular"]}
{"id": "hf-dataset:nebula/GenImage-arrow", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nebula/GenImage-arrow", "date": "2025-04-07", "createdAt": "2025-04-07", "sourceUpdatedAt": "2025-04-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 74527 downloads.", "popularity": {"value": 74527, "label": "downloads"}, "url": "https://huggingface.co/datasets/nebula/GenImage-arrow", "tags": ["datasets", "format:arrow", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:tabular", "modality:text", "region:us"]}
{"id": "hf-dataset:TIGER-Lab/arxiv-latex-5T", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "TIGER-Lab/arxiv-latex-5T", "date": "2025-04-17", "createdAt": "2025-04-05", "sourceUpdatedAt": "2025-04-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 290548 downloads.", "popularity": {"value": 290548, "label": "downloads"}, "url": "https://huggingface.co/datasets/TIGER-Lab/arxiv-latex-5T", "tags": ["datasets", "format:webdataset", "language:en", "library:datasets", "library:mlcroissant", "library:webdataset", "license:apache-2.0", "modality:image"]}
{"id": "github:sylphxai/pdf-reader-mcp", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SylphxAI/pdf-reader-mcp", "date": "2026-06-01", "createdAt": "2025-04-04", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📄 Production-ready MCP server for PDF processing - 5-10x faster with parallel processing and 94%+ test coverage", "popularity": {"value": 753, "label": "stars"}, "url": "https://github.com/SylphxAI/pdf-reader-mcp", "tags": ["ai-tools", "rag"]}
{"id": "github:unbody-io/unbody", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "unbody-io/unbody", "date": "2026-04-14", "createdAt": "2025-04-02", "sourceUpdatedAt": "2026-04-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data.", "popularity": {"value": 528, "label": "stars"}, "url": "https://github.com/unbody-io/unbody", "tags": ["tools", "vector-database"]}
{"id": "github:vectifyai/pageindex", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "VectifyAI/PageIndex", "date": "2026-06-03", "createdAt": "2025-04-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG", "popularity": {"value": 32503, "label": "stars"}, "url": "https://github.com/VectifyAI/PageIndex", "tags": ["llm", "rag"]}
{"id": "github:bytedance/uno", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bytedance/UNO", "date": "2025-09-12", "createdAt": "2025-04-01", "sourceUpdatedAt": "2025-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[ICCV 2025] 🔥🔥  UNO: A Universal Customization Method for Both Single and Multi-Subject Conditioning", "popularity": {"value": 1356, "label": "stars"}, "url": "https://github.com/bytedance/UNO", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:updatebao/geonamebase_1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "updatebao/geonamebase_1", "date": "2025-06-15", "createdAt": "2025-04-01", "sourceUpdatedAt": "2025-06-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 405978 downloads.", "popularity": {"value": 405978, "label": "downloads"}, "url": "https://huggingface.co/datasets/updatebao/geonamebase_1", "tags": ["datasets", "modality:image", "region:us"]}
{"id": "hf-dataset:Genesis-Intelligence/assets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Genesis-Intelligence/assets", "date": "2026-06-01", "createdAt": "2025-03-31", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73653 downloads.", "popularity": {"value": 73653, "label": "downloads"}, "url": "https://huggingface.co/datasets/Genesis-Intelligence/assets", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:mit", "modality:3d", "modality:image", "region:us"]}
{"id": "github:aliasrobotics/cai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "aliasrobotics/cai", "date": "2026-06-01", "createdAt": "2025-03-31", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Cybersecurity AI (CAI), the framework for AI Security", "popularity": {"value": 8822, "label": "stars"}, "url": "https://github.com/aliasrobotics/cai", "tags": ["generative-ai", "tools"]}
{"id": "github:humanlayer/12-factor-agents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "humanlayer/12-factor-agents", "date": "2025-09-21", "createdAt": "2025-03-30", "sourceUpdatedAt": "2025-09-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?", "popularity": {"value": 22971, "label": "stars"}, "url": "https://github.com/humanlayer/12-factor-agents", "tags": ["agents", "rag"]}
{"id": "hf-dataset:LLM360/MegaMath", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "LLM360/MegaMath", "date": "2025-04-09", "createdAt": "2025-03-30", "sourceUpdatedAt": "2025-04-09", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47553 downloads.", "popularity": {"value": 47553, "label": "downloads"}, "url": "https://huggingface.co/datasets/LLM360/MegaMath", "tags": ["arxiv:2504.02807", "code", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:tasl-lab/uniocc", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tasl-lab/uniocc", "date": "2025-08-19", "createdAt": "2025-03-27", "sourceUpdatedAt": "2025-08-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 316097 downloads.", "popularity": {"value": 316097, "label": "downloads"}, "url": "https://huggingface.co/datasets/tasl-lab/uniocc", "tags": ["3d", "3d-occupancy", "arxiv:2503.24381", "autonomous-driving", "benchmark", "carla", "datasets", "flow-estimation"]}
{"id": "github:upstash/context7", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "upstash/context7", "date": "2026-06-03", "createdAt": "2025-03-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors", "popularity": {"value": 56681, "label": "stars"}, "url": "https://github.com/upstash/context7", "tags": ["llm", "tools"]}
{"id": "github:a2aproject/a2a", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "a2aproject/A2A", "date": "2026-06-02", "createdAt": "2025-03-25", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.", "popularity": {"value": 24113, "label": "stars"}, "url": "https://github.com/a2aproject/A2A", "tags": ["agents", "generative-ai"]}
{"id": "hf-dataset:rishitdagli/nerf-gs-datasets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rishitdagli/nerf-gs-datasets", "date": "2025-03-29", "createdAt": "2025-03-25", "sourceUpdatedAt": "2025-03-29", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 50230 downloads.", "popularity": {"value": 50230, "label": "downloads"}, "url": "https://huggingface.co/datasets/rishitdagli/nerf-gs-datasets", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:1k<n<10k"]}
{"id": "github:truffle-ai/dexto", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "truffle-ai/dexto", "date": "2026-06-03", "createdAt": "2025-03-24", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A coding agent and general agent harness for building and orchestrating agentic applications.", "popularity": {"value": 630, "label": "stars"}, "url": "https://github.com/truffle-ai/dexto", "tags": ["agents", "ai-tools"]}
{"id": "github:allweonedev/presentation-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "allweonedev/presentation-ai", "date": "2026-04-04", "createdAt": "2025-03-24", "sourceUpdatedAt": "2026-04-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ALLWEONE® Open source AI presentation generator Gamma Alternative. Create professional slides with customizable themes and AI-generated content in minutes.", "popularity": {"value": 2842, "label": "stars"}, "url": "https://github.com/allweonedev/presentation-ai", "tags": ["generative-ai", "tools"]}
{"id": "github:mcp-router/mcp-router", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mcp-router/mcp-router", "date": "2026-01-24", "createdAt": "2025-03-22", "sourceUpdatedAt": "2026-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A Unified MCP Server Management App (MCP Manager).", "popularity": {"value": 2031, "label": "stars"}, "url": "https://github.com/mcp-router/mcp-router", "tags": ["llmops", "tools"]}
{"id": "github:utensils/mcp-nixos", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "utensils/mcp-nixos", "date": "2026-06-04", "createdAt": "2025-03-20", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "MCP-NixOS - Model Context Protocol Server for NixOS resources", "popularity": {"value": 659, "label": "stars"}, "url": "https://github.com/utensils/mcp-nixos", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:dw-dengwei/daily-arxiv-ai-enhanced", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dw-dengwei/daily-arXiv-ai-enhanced", "date": "2026-06-03", "createdAt": "2025-03-20", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Automatically crawl arXiv papers daily and summarize them using AI. Illustrating them using GitHub Pages.", "popularity": {"value": 2805, "label": "stars"}, "url": "https://github.com/dw-dengwei/daily-arXiv-ai-enhanced", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:maximhq/bifrost", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "maximhq/bifrost", "date": "2026-06-04", "createdAt": "2025-03-19", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fastest enterprise AI gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.", "popularity": {"value": 5466, "label": "stars"}, "url": "https://github.com/maximhq/bifrost", "tags": ["llmops", "tools"]}
{"id": "hf-dataset:nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "date": "2026-03-05", "createdAt": "2025-03-18", "sourceUpdatedAt": "2026-03-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 338337 downloads.", "popularity": {"value": 338337, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim", "tags": ["datasets", "license:cc-by-4.0", "region:us", "robotics", "task_categories:robotics"]}
{"id": "hf-dataset:AudioLLMs/Multitask-National-Speech-Corpus-v1-extend", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AudioLLMs/Multitask-National-Speech-Corpus-v1-extend", "date": "2025-03-31", "createdAt": "2025-03-18", "sourceUpdatedAt": "2025-03-31", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 52273 downloads.", "popularity": {"value": 52273, "label": "downloads"}, "url": "https://huggingface.co/datasets/AudioLLMs/Multitask-National-Speech-Corpus-v1-extend", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:audio", "modality:text"]}
{"id": "hf-dataset:cadene/droid_1.0.1", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cadene/droid_1.0.1", "date": "2025-03-20", "createdAt": "2025-03-17", "sourceUpdatedAt": "2025-03-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 437209 downloads.", "popularity": {"value": 437209, "label": "downloads"}, "url": "https://huggingface.co/datasets/cadene/droid_1.0.1", "tags": ["datasets", "lerobot", "license:apache-2.0", "region:us", "task_categories:robotics"]}
{"id": "github:getbindu/bindu", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "GetBindu/Bindu", "date": "2026-06-02", "createdAt": "2025-03-16", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Bindu: The identity, communication, and payments layer for AI agents.", "popularity": {"value": 6809, "label": "stars"}, "url": "https://github.com/GetBindu/Bindu", "tags": ["agents", "ai-agent"]}
{"id": "github:grab/cursor-talk-to-figma-mcp", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "grab/cursor-talk-to-figma-mcp", "date": "2026-04-29", "createdAt": "2025-03-16", "sourceUpdatedAt": "2026-04-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "TalkToFigma: MCP integration between AI Agent (Cursor, Claude Code) and Figma, allowing Agentic AI to communicate with Figma for reading designs and modifying them programmatically.", "popularity": {"value": 6810, "label": "stars"}, "url": "https://github.com/grab/cursor-talk-to-figma-mcp", "tags": ["generative-ai", "ui-demo"]}
{"id": "hf-dataset:filapro/cad-recode-v1.5", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "filapro/cad-recode-v1.5", "date": "2025-03-16", "createdAt": "2025-03-16", "sourceUpdatedAt": "2025-03-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 83727 downloads.", "popularity": {"value": 83727, "label": "downloads"}, "url": "https://huggingface.co/datasets/filapro/cad-recode-v1.5", "tags": ["arxiv:2412.14042", "datasets", "license:cc-by-nc-4.0", "region:us"]}
{"id": "hf-dataset:Vchitect/Vchitect_T2V_DataVerse", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Vchitect/Vchitect_T2V_DataVerse", "date": "2025-03-27", "createdAt": "2025-03-14", "sourceUpdatedAt": "2025-03-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 47848 downloads.", "popularity": {"value": 47848, "label": "downloads"}, "url": "https://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse", "tags": ["arxiv:2501.08453", "datasets", "format:webdataset", "library:datasets", "library:mlcroissant", "library:webdataset", "license:apache-2.0", "modality:text"]}
{"id": "hf-dataset:baber/piqa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "baber/piqa", "date": "2025-03-14", "createdAt": "2025-03-14", "sourceUpdatedAt": "2025-03-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 140513 downloads.", "popularity": {"value": 140513, "label": "downloads"}, "url": "https://huggingface.co/datasets/baber/piqa", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:filipecalegario/awesome-vibe-coding", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "filipecalegario/awesome-vibe-coding", "date": "2026-04-16", "createdAt": "2025-03-13", "sourceUpdatedAt": "2026-04-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of vibe coding references, collaborating with AI to write code.", "popularity": {"value": 4645, "label": "stars"}, "url": "https://github.com/filipecalegario/awesome-vibe-coding", "tags": ["agents", "ai-agent"]}
{"id": "github:openai/openai-agents-python", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "openai/openai-agents-python", "date": "2026-05-31", "createdAt": "2025-03-11", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A lightweight, powerful framework for multi-agent workflows", "popularity": {"value": 26894, "label": "stars"}, "url": "https://github.com/openai/openai-agents-python", "tags": ["agents", "llm"]}
{"id": "hf-dataset:merve/vlm_test_images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "merve/vlm_test_images", "date": "2026-04-02", "createdAt": "2025-03-10", "sourceUpdatedAt": "2026-04-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47514 downloads.", "popularity": {"value": 47514, "label": "downloads"}, "url": "https://huggingface.co/datasets/merve/vlm_test_images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:image", "modality:video", "region:us"]}
{"id": "github:souvikmajumder26/multi-agent-medical-assistant", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "souvikmajumder26/Multi-Agent-Medical-Assistant", "date": "2025-05-03", "createdAt": "2025-03-10", "sourceUpdatedAt": "2025-05-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "⚕️GenAI powered multi-agentic medical diagnostics and healthcare research assistance chatbot. 🏥 Designed for healthcare professionals, researchers and patients.", "popularity": {"value": 898, "label": "stars"}, "url": "https://github.com/souvikmajumder26/Multi-Agent-Medical-Assistant", "tags": ["agents", "vector-database"]}
{"id": "hf-dataset:IPEC-COMMUNITY/language_table_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/language_table_lerobot", "date": "2025-03-20", "createdAt": "2025-03-10", "sourceUpdatedAt": "2025-03-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 170804 downloads.", "popularity": {"value": 170804, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/language_table_lerobot", "tags": ["datasets", "language_table", "lerobot", "license:apache-2.0", "openx", "region:us", "rlds", "task_categories:robotics"]}
{"id": "github:kalyanks-nlp/llm-engineer-toolkit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "KalyanKS-NLP/llm-engineer-toolkit", "date": "2026-05-23", "createdAt": "2025-03-09", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of  120+ LLM libraries category wise.", "popularity": {"value": 10382, "label": "stars"}, "url": "https://github.com/KalyanKS-NLP/llm-engineer-toolkit", "tags": ["developer-tools", "generative-ai"]}
{"id": "hf-dataset:jobs-git/HPLT2.0_cleaned", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jobs-git/HPLT2.0_cleaned", "date": "2025-03-07", "createdAt": "2025-03-07", "sourceUpdatedAt": "2025-03-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 200381 downloads.", "popularity": {"value": 200381, "label": "downloads"}, "url": "https://huggingface.co/datasets/jobs-git/HPLT2.0_cleaned", "tags": ["datasets", "language:ace", "language:af", "language:als", "language:am", "language:ar", "language:as", "language:ast"]}
{"id": "hf-dataset:jobs-git/Zyda-2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jobs-git/Zyda-2", "date": "2025-03-07", "createdAt": "2025-03-07", "sourceUpdatedAt": "2025-03-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 187694 downloads.", "popularity": {"value": 187694, "label": "downloads"}, "url": "https://huggingface.co/datasets/jobs-git/Zyda-2", "tags": ["datasets", "language:en", "license:odc-by", "region:us", "size_categories:n>1t", "task_categories:text-generation"]}
{"id": "hf-dataset:openbmb/Ultra-FineWeb", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "openbmb/Ultra-FineWeb", "date": "2026-05-28", "createdAt": "2025-03-06", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 84296 downloads.", "popularity": {"value": 84296, "label": "downloads"}, "url": "https://huggingface.co/datasets/openbmb/Ultra-FineWeb", "tags": ["arxiv:2412.04315", "arxiv:2505.05427", "arxiv:2602.09003", "data-filtering", "datasets", "format:parquet", "high-quality", "language:en"]}
{"id": "hf-model:sesame/csm-1b", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sesame/csm-1b", "date": "2025-03-06", "createdAt": "2025-03-06", "sourceUpdatedAt": "2025-03-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 253372 downloads and tags: transformers, safetensors, csm, text-to-audio.", "popularity": {"value": 253372, "label": "downloads"}, "url": "https://huggingface.co/sesame/csm-1b", "tags": ["audio", "csm", "en", "endpoints_compatible", "license:apache-2.0", "safetensors", "text-to-audio", "text-to-speech"]}
{"id": "github:conardli/easy-dataset", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ConardLi/easy-dataset", "date": "2026-05-01", "createdAt": "2025-03-04", "sourceUpdatedAt": "2026-05-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval", "popularity": {"value": 14396, "label": "stars"}, "url": "https://github.com/ConardLi/easy-dataset", "tags": ["rag"]}
{"id": "github:cocoindex-io/cocoindex", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "cocoindex-io/cocoindex", "date": "2026-06-03", "createdAt": "2025-03-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Incremental engine for long horizon agents 🌟 Star if you like it!", "popularity": {"value": 10168, "label": "stars"}, "url": "https://github.com/cocoindex-io/cocoindex", "tags": ["agents", "rag"]}
{"id": "github:neuron-core/neuron-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "neuron-core/neuron-ai", "date": "2026-06-03", "createdAt": "2025-03-02", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The PHP Agentic Framework to build production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data.", "popularity": {"value": 1951, "label": "stars"}, "url": "https://github.com/neuron-core/neuron-ai", "tags": ["vector-database", "vector-db"]}
{"id": "github:suyoumo/clawprobench", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "suyoumo/ClawProBench", "date": "2026-05-19", "createdAt": "2025-03-02", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ClawProBench is a live-first benchmark harness for evaluating LLM agents   in the OpenClaw runtime with deterministic grading and repeated-trial   reliability.", "popularity": {"value": 695, "label": "stars"}, "url": "https://github.com/suyoumo/ClawProBench", "tags": ["agents", "evaluation"]}
{"id": "hf-dataset:RichardErkhov/DASP", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "RichardErkhov/DASP", "date": "2025-03-09", "createdAt": "2025-03-02", "sourceUpdatedAt": "2025-03-09", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 48266 downloads.", "popularity": {"value": 48266, "label": "downloads"}, "url": "https://huggingface.co/datasets/RichardErkhov/DASP", "tags": ["datasets", "earth-observation", "geospatial", "license:cc-by-sa-3.0", "modality:geospatial", "region:us", "remote-sensing", "satellite-imagery"]}
{"id": "hf-model:mlx-community/Kokoro-82M-bf16", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "mlx-community/Kokoro-82M-bf16", "date": "2025-02-28", "createdAt": "2025-02-28", "sourceUpdatedAt": "2025-02-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 498627 downloads and tags: mlx, text-to-speech, en, base_model:yl4579/StyleTTS2-LJSpeech.", "popularity": {"value": 498627, "label": "downloads"}, "url": "https://huggingface.co/mlx-community/Kokoro-82M-bf16", "tags": ["audio", "base_model:finetune:yl4579/styletts2-ljspeech", "base_model:yl4579/styletts2-ljspeech", "en", "license:apache-2.0", "mlx", "region:us", "text-to-speech"]}
{"id": "github:foundationvision/unitok", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "FoundationVision/UniTok", "date": "2025-11-14", "createdAt": "2025-02-27", "sourceUpdatedAt": "2025-11-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[NeurIPS 2025 Spotlight] A Unified Tokenizer for Visual Generation and Understanding", "popularity": {"value": 525, "label": "stars"}, "url": "https://github.com/FoundationVision/UniTok", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:IPEC-COMMUNITY/droid_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/droid_lerobot", "date": "2025-04-28", "createdAt": "2025-02-26", "sourceUpdatedAt": "2025-04-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 501093 downloads.", "popularity": {"value": 501093, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/droid_lerobot", "tags": ["datasets", "droid", "franka", "lerobot", "license:apache-2.0", "openx", "region:us", "rlds"]}
{"id": "hf-dataset:IPEC-COMMUNITY/kuka_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/kuka_lerobot", "date": "2025-02-24", "createdAt": "2025-02-23", "sourceUpdatedAt": "2025-02-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54887 downloads.", "popularity": {"value": 54887, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/kuka_lerobot", "tags": ["datasets", "kuka", "kuka_iiwa", "lerobot", "license:apache-2.0", "modality:video", "openx", "region:us"]}
{"id": "hf-dataset:cadene/droid", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cadene/droid", "date": "2025-02-27", "createdAt": "2025-02-22", "sourceUpdatedAt": "2025-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 157788 downloads.", "popularity": {"value": 157788, "label": "downloads"}, "url": "https://huggingface.co/datasets/cadene/droid", "tags": ["arxiv:2403.12945", "datasets", "language:en", "lerobot", "license:apache-2.0", "modality:video", "openx", "region:us"]}
{"id": "hf-dataset:IPEC-COMMUNITY/bridge_orig_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/bridge_orig_lerobot", "date": "2025-02-23", "createdAt": "2025-02-22", "sourceUpdatedAt": "2025-02-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 731420 downloads.", "popularity": {"value": 731420, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/bridge_orig_lerobot", "tags": ["bridge_orig", "datasets", "lerobot", "license:apache-2.0", "modality:video", "openx", "region:us", "rlds"]}
{"id": "github:seekingdream/static-to-dynamic-llmeval", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SeekingDream/Static-to-Dynamic-LLMEval", "date": "2026-03-03", "createdAt": "2025-02-21", "sourceUpdatedAt": "2026-03-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The official GitHub repository of the paper \"Recent advances in large language model benchmarks against data contamination: From static to dynamic evaluation\"", "popularity": {"value": 498, "label": "stars"}, "url": "https://github.com/SeekingDream/Static-to-Dynamic-LLMEval", "tags": ["evaluation"]}
{"id": "hf-dataset:updatebao/country", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "updatebao/country", "date": "2025-02-21", "createdAt": "2025-02-21", "sourceUpdatedAt": "2025-02-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62563 downloads.", "popularity": {"value": 62563, "label": "downloads"}, "url": "https://huggingface.co/datasets/updatebao/country", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:1k<n<10k"]}
{"id": "hf-dataset:hiyouga/geometry3k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hiyouga/geometry3k", "date": "2025-04-14", "createdAt": "2025-02-20", "sourceUpdatedAt": "2025-04-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51882 downloads.", "popularity": {"value": 51882, "label": "downloads"}, "url": "https://huggingface.co/datasets/hiyouga/geometry3k", "tags": ["datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "github:fosowl/agenticseek", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Fosowl/agenticSeek", "date": "2026-05-17", "createdAt": "2025-02-19", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fully Local Manus AI. No APIs, No $200 monthly bills. Enjoy an autonomous agent that thinks, browses the web, and code for the sole cost of electricity. 🔔 Official updates only via twitter @Martin993886460 (Beware of fake account)", "popularity": {"value": 26451, "label": "stars"}, "url": "https://github.com/Fosowl/agenticSeek", "tags": ["agents", "llm"]}
{"id": "hf-dataset:dinofamily529/malaysia_legal", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "dinofamily529/malaysia_legal", "date": "2025-02-19", "createdAt": "2025-02-19", "sourceUpdatedAt": "2025-02-19", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47183 downloads.", "popularity": {"value": 47183, "label": "downloads"}, "url": "https://huggingface.co/datasets/dinofamily529/malaysia_legal", "tags": ["datasets", "format:csv", "language:en", "language:ms", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:IPEC-COMMUNITY/fractal20220817_data_lerobot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "IPEC-COMMUNITY/fractal20220817_data_lerobot", "date": "2025-02-23", "createdAt": "2025-02-18", "sourceUpdatedAt": "2025-02-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 139952 downloads.", "popularity": {"value": 139952, "label": "downloads"}, "url": "https://huggingface.co/datasets/IPEC-COMMUNITY/fractal20220817_data_lerobot", "tags": ["datasets", "fractal20220817_data", "google_robot", "lerobot", "license:apache-2.0", "modality:video", "openx", "region:us"]}
{"id": "hf-dataset:math-ai/aime25", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "math-ai/aime25", "date": "2026-01-19", "createdAt": "2025-02-17", "sourceUpdatedAt": "2026-01-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 90991 downloads.", "popularity": {"value": 90991, "label": "downloads"}, "url": "https://huggingface.co/datasets/math-ai/aime25", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:apache-2.0", "modality:text"]}
{"id": "github:miantiao-me/hacker-podcast", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "miantiao-me/hacker-podcast", "date": "2026-05-09", "createdAt": "2025-02-15", "sourceUpdatedAt": "2026-05-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "一个基于 AI 的 Hacker News 中文播客项目，每天自动抓取 Hacker News 热门文章，通过 AI 生成中文总结并转换为播客内容。", "popularity": {"value": 2537, "label": "stars"}, "url": "https://github.com/miantiao-me/hacker-podcast", "tags": ["agents", "ai-agent"]}
{"id": "github:bytedance/infiniteyou", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bytedance/InfiniteYou", "date": "2025-08-22", "createdAt": "2025-02-14", "sourceUpdatedAt": "2025-08-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔥 [ICCV 2025 Highlight] InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity", "popularity": {"value": 2682, "label": "stars"}, "url": "https://github.com/bytedance/InfiniteYou", "tags": ["inference", "text-to-image"]}
{"id": "github:liyupi/ai-guide", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "liyupi/ai-guide", "date": "2026-05-25", "createdAt": "2025-02-13", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude）、最新 AI 资讯、Prompt 提示词大全、AI 知识百科（Agent Skills / RAG / MCP / A2A）、AI 编程教程（Harness Engineering）、AI 工具用法（Cursor / Claude Code / TRAE / Codex / Copilot）、AI 开发框架教程（Spring A...", "popularity": {"value": 15119, "label": "stars"}, "url": "https://github.com/liyupi/ai-guide", "tags": ["agents", "rag"]}
{"id": "hf-dataset:amphora/euler-math-logs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "amphora/euler-math-logs", "date": "2025-02-13", "createdAt": "2025-02-13", "sourceUpdatedAt": "2025-02-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71150 downloads.", "popularity": {"value": 71150, "label": "downloads"}, "url": "https://huggingface.co/datasets/amphora/euler-math-logs", "tags": ["datasets", "region:us"]}
{"id": "github:linshenkx/prompt-optimizer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "linshenkx/prompt-optimizer", "date": "2026-06-02", "createdAt": "2025-02-12", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An AI prompt optimizer for writing better prompts and getting better AI results.", "popularity": {"value": 30390, "label": "stars"}, "url": "https://github.com/linshenkx/prompt-optimizer", "tags": ["llm", "tools"]}
{"id": "github:1517005260/graph-rag-agent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "1517005260/graph-rag-agent", "date": "2025-11-05", "createdAt": "2025-02-12", "sourceUpdatedAt": "2025-11-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "拼好RAG：手搓并融合了GraphRAG、LightRAG、Neo4j-llm-graph-builder进行知识图谱构建以及搜索；整合DeepSearch技术实现私域RAG的推理；自制针对GraphRAG的评估框架| Integrate GraphRAG, LightRAG, and Neo4j-llm-graph-builder for knowledge graph construction and search. Combine DeepSearch for private RAG reasoning...", "popularity": {"value": 2197, "label": "stars"}, "url": "https://github.com/1517005260/graph-rag-agent", "tags": ["agents", "evaluation"]}
{"id": "hf-dataset:open-r1/OpenR1-Math-220k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "open-r1/OpenR1-Math-220k", "date": "2025-02-18", "createdAt": "2025-02-10", "sourceUpdatedAt": "2025-02-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49983 downloads.", "popularity": {"value": 49983, "label": "downloads"}, "url": "https://huggingface.co/datasets/open-r1/OpenR1-Math-220k", "tags": ["datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:apache-2.0"]}
{"id": "github:groupultra/telegram-search", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "groupultra/telegram-search", "date": "2026-06-03", "createdAt": "2025-02-08", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔍 导出并模糊搜索 Telegram 聊天记录 | Export and fuzzy search your Telegram chat history", "popularity": {"value": 3912, "label": "stars"}, "url": "https://github.com/groupultra/telegram-search", "tags": ["agents", "ai-agent"]}
{"id": "github:zilliztech/deep-searcher", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zilliztech/deep-searcher", "date": "2025-11-19", "createdAt": "2025-02-08", "sourceUpdatedAt": "2025-11-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.", "popularity": {"value": 7849, "label": "stars"}, "url": "https://github.com/zilliztech/deep-searcher", "tags": ["rag"]}
{"id": "hf-model:onnx-community/Kokoro-82M-v1.0-ONNX", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "onnx-community/Kokoro-82M-v1.0-ONNX", "date": "2025-02-07", "createdAt": "2025-02-07", "sourceUpdatedAt": "2025-02-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 634750 downloads and tags: transformers.js, onnx, style_text_to_speech_2, text-to-speech.", "popularity": {"value": 634750, "label": "downloads"}, "url": "https://huggingface.co/onnx-community/Kokoro-82M-v1.0-ONNX", "tags": ["audio", "base_model:hexgrad/kokoro-82m", "base_model:quantized:hexgrad/kokoro-82m", "en", "license:apache-2.0", "onnx", "style_text_to_speech_2", "text-to-speech"]}
{"id": "hf-dataset:Anthropic/EconomicIndex", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Anthropic/EconomicIndex", "date": "2026-05-21", "createdAt": "2025-02-06", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51343 downloads.", "popularity": {"value": 51343, "label": "downloads"}, "url": "https://huggingface.co/datasets/Anthropic/EconomicIndex", "tags": ["ai", "anthropic", "arxiv:2503.04761", "datasets", "economic impacts", "language:en", "license:mit", "llm"]}
{"id": "github:bytebot-ai/bytebot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bytebot-ai/bytebot", "date": "2025-09-12", "createdAt": "2025-02-03", "sourceUpdatedAt": "2025-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands, operating within a containerized Linux desktop environment.", "popularity": {"value": 11040, "label": "stars"}, "url": "https://github.com/bytebot-ai/bytebot", "tags": ["agents", "ai-tools"]}
{"id": "github:trycua/cua", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "trycua/cua", "date": "2026-06-04", "createdAt": "2025-01-31", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).", "popularity": {"value": 17595, "label": "stars"}, "url": "https://github.com/trycua/cua", "tags": ["agents", "ai-agent"]}
{"id": "github:kreuzberg-dev/kreuzberg", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "kreuzberg-dev/kreuzberg", "date": "2026-06-04", "createdAt": "2025-01-31", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured information from PDFs, Office documents, images, and 97+ formats. Available for Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, R, C, TypeScript (Node...", "popularity": {"value": 8437, "label": "stars"}, "url": "https://github.com/kreuzberg-dev/kreuzberg", "tags": ["rag"]}
{"id": "github:googlecloudplatform/agent-starter-pack", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "GoogleCloudPlatform/agent-starter-pack", "date": "2026-06-01", "createdAt": "2025-01-31", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.", "popularity": {"value": 6459, "label": "stars"}, "url": "https://github.com/GoogleCloudPlatform/agent-starter-pack", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:JianZhangAI/hoi4d-depth", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "JianZhangAI/hoi4d-depth", "date": "2025-02-02", "createdAt": "2025-01-31", "sourceUpdatedAt": "2025-02-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 111079 downloads.", "popularity": {"value": 111079, "label": "downloads"}, "url": "https://huggingface.co/datasets/JianZhangAI/hoi4d-depth", "tags": ["datasets", "format:webdataset", "library:datasets", "library:mlcroissant", "library:webdataset", "modality:text", "region:us", "size_categories:1k<n<10k"]}
{"id": "github:vllm-project/vllm-ascend", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vllm-project/vllm-ascend", "date": "2026-06-04", "createdAt": "2025-01-29", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Community maintained hardware plugin for vLLM on Ascend", "popularity": {"value": 2187, "label": "stars"}, "url": "https://github.com/vllm-project/vllm-ascend", "tags": ["inference"]}
{"id": "hf-dataset:fhswf/dgs-pose", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fhswf/dgs-pose", "date": "2026-03-12", "createdAt": "2025-01-28", "sourceUpdatedAt": "2026-03-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 264512 downloads.", "popularity": {"value": 264512, "label": "downloads"}, "url": "https://huggingface.co/datasets/fhswf/dgs-pose", "tags": ["datasets", "german-sign-language", "gesture-recognition", "language:gsg", "license:mit", "pose-estimation", "region:us", "sign-language"]}
{"id": "hf-dataset:open-thoughts/OpenThoughts-114k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "open-thoughts/OpenThoughts-114k", "date": "2025-08-31", "createdAt": "2025-01-27", "sourceUpdatedAt": "2025-08-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 104990 downloads.", "popularity": {"value": 104990, "label": "downloads"}, "url": "https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k", "tags": ["arxiv:2506.04178", "curator", "datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:SwayStar123/preprocessed_commoncatalog-cc-by_DCAE", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SwayStar123/preprocessed_commoncatalog-cc-by_DCAE", "date": "2025-01-29", "createdAt": "2025-01-24", "sourceUpdatedAt": "2025-01-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 91348 downloads.", "popularity": {"value": 91348, "label": "downloads"}, "url": "https://huggingface.co/datasets/SwayStar123/preprocessed_commoncatalog-cc-by_DCAE", "tags": ["datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:cc"]}
{"id": "github:cyanheads/obsidian-mcp-server", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "cyanheads/obsidian-mcp-server", "date": "2026-06-02", "createdAt": "2025-01-23", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Obsidian vaults MCP server - read, write, search, and surgically edit notes, tags, and frontmatter via the Local REST API plugin.", "popularity": {"value": 572, "label": "stars"}, "url": "https://github.com/cyanheads/obsidian-mcp-server", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:agents-course/course-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "agents-course/course-images", "date": "2025-06-20", "createdAt": "2025-01-23", "sourceUpdatedAt": "2025-06-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 228691 downloads.", "popularity": {"value": 228691, "label": "downloads"}, "url": "https://huggingface.co/datasets/agents-course/course-images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:HuggingFaceH4/aime_2024", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceH4/aime_2024", "date": "2025-01-26", "createdAt": "2025-01-23", "sourceUpdatedAt": "2025-01-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 60770 downloads.", "popularity": {"value": 60770, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceH4/aime_2024", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:meihualuomanxueshan/matrixcity_large_folder", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "meihualuomanxueshan/matrixcity_large_folder", "date": "2025-01-24", "createdAt": "2025-01-23", "sourceUpdatedAt": "2025-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 127200 downloads.", "popularity": {"value": 127200, "label": "downloads"}, "url": "https://huggingface.co/datasets/meihualuomanxueshan/matrixcity_large_folder", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "hf-dataset:meihualuomanxueshan/matrixcity_large_folder_dense", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "meihualuomanxueshan/matrixcity_large_folder_dense", "date": "2025-01-24", "createdAt": "2025-01-23", "sourceUpdatedAt": "2025-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 103891 downloads.", "popularity": {"value": 103891, "label": "downloads"}, "url": "https://huggingface.co/datasets/meihualuomanxueshan/matrixcity_large_folder_dense", "tags": ["datasets", "license:apache-2.0", "region:us"]}
{"id": "github:snap-research/stable-flow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "snap-research/stable-flow", "date": "2025-06-08", "createdAt": "2025-01-22", "sourceUpdatedAt": "2025-06-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official implementation for \"Stable Flow: Vital Layers for Training-Free Image Editing\" [CVPR 2025]", "popularity": {"value": 406, "label": "stars"}, "url": "https://github.com/snap-research/stable-flow", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:deepseek-ai/DeepSeek-R1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "deepseek-ai/DeepSeek-R1", "date": "2025-01-20", "createdAt": "2025-01-20", "sourceUpdatedAt": "2025-01-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5536340 downloads and tags: transformers, safetensors, deepseek_v3, text-generation.", "popularity": {"value": 5536340, "label": "downloads"}, "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1", "tags": ["arxiv:2501.12948", "coding", "conversational", "custom_code", "deepseek_v3", "license:mit", "safetensors", "text-generation"]}
{"id": "hf-dataset:zeroMN/hanlp_date-zh", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "zeroMN/hanlp_date-zh", "date": "2025-01-20", "createdAt": "2025-01-20", "sourceUpdatedAt": "2025-01-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 126790 downloads.", "popularity": {"value": 126790, "label": "downloads"}, "url": "https://huggingface.co/datasets/zeroMN/hanlp_date-zh", "tags": ["code", "datasets", "language:zh", "license:mit", "region:us", "size_categories:100m<n<1b", "task_categories:text-classification"]}
{"id": "github:openbmb/ultrarag", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "OpenBMB/UltraRAG", "date": "2026-06-04", "createdAt": "2025-01-16", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines", "popularity": {"value": 5578, "label": "stars"}, "url": "https://github.com/OpenBMB/UltraRAG", "tags": ["rag"]}
{"id": "github:isi-dev/google-colab_notebooks", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Isi-dev/Google-Colab_Notebooks", "date": "2026-05-22", "createdAt": "2025-01-16", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A Collection of Google Colab Notebooks for various projects", "popularity": {"value": 473, "label": "stars"}, "url": "https://github.com/Isi-dev/Google-Colab_Notebooks", "tags": ["text-to-image", "tools"]}
{"id": "github:rowboatlabs/rowboat", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "rowboatlabs/rowboat", "date": "2026-06-03", "createdAt": "2025-01-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source AI coworker, with memory", "popularity": {"value": 14886, "label": "stars"}, "url": "https://github.com/rowboatlabs/rowboat", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:CMLI-NLP/CUTE-Datasets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CMLI-NLP/CUTE-Datasets", "date": "2025-06-19", "createdAt": "2025-01-13", "sourceUpdatedAt": "2025-06-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52046 downloads.", "popularity": {"value": 52046, "label": "downloads"}, "url": "https://huggingface.co/datasets/CMLI-NLP/CUTE-Datasets", "tags": ["datasets", "format:text", "language:bo", "language:en", "language:ug", "language:zh", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:Benjy/typed_digital_signatures", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Benjy/typed_digital_signatures", "date": "2025-02-05", "createdAt": "2025-01-13", "sourceUpdatedAt": "2025-02-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 291827 downloads.", "popularity": {"value": 291827, "label": "downloads"}, "url": "https://huggingface.co/datasets/Benjy/typed_digital_signatures", "tags": ["computer-vision", "datasets", "digital-signatures", "google-fonts", "handwriting", "image-classification", "language:en", "license:mit"]}
{"id": "hf-dataset:jamesqijingsong/zidian", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jamesqijingsong/zidian", "date": "2025-01-30", "createdAt": "2025-01-11", "sourceUpdatedAt": "2025-01-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 92544 downloads.", "popularity": {"value": 92544, "label": "downloads"}, "url": "https://huggingface.co/datasets/jamesqijingsong/zidian", "tags": ["art", "datasets", "format:imagefolder", "image", "language:en", "language:zh", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:jamesqijingsong/chengyu", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jamesqijingsong/chengyu", "date": "2025-01-25", "createdAt": "2025-01-11", "sourceUpdatedAt": "2025-01-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 84556 downloads.", "popularity": {"value": 84556, "label": "downloads"}, "url": "https://huggingface.co/datasets/jamesqijingsong/chengyu", "tags": ["art", "chengyu", "datasets", "dictionary", "image", "language:en", "language:zh", "license:cc-by-nc-4.0"]}
{"id": "hf-model:cagliostrolab/animagine-xl-4.0", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "cagliostrolab/animagine-xl-4.0", "date": "2025-01-10", "createdAt": "2025-01-10", "sourceUpdatedAt": "2025-01-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 260916 downloads and tags: diffusers, safetensors, text-to-image, stable-diffusion.", "popularity": {"value": 260916, "label": "downloads"}, "url": "https://huggingface.co/cagliostrolab/animagine-xl-4.0", "tags": ["base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "diffusers", "en", "image-generation", "safetensors", "stable-diffusion", "stable-diffusion-xl"]}
{"id": "github:simstudioai/sim", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "simstudioai/sim", "date": "2026-06-04", "createdAt": "2025-01-05", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.", "popularity": {"value": 28695, "label": "stars"}, "url": "https://github.com/simstudioai/sim", "tags": ["agents", "rag"]}
{"id": "hf-dataset:morteza20/mteb_leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "morteza20/mteb_leaderboard", "date": "2025-01-04", "createdAt": "2025-01-04", "sourceUpdatedAt": "2025-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50609 downloads.", "popularity": {"value": 50609, "label": "downloads"}, "url": "https://huggingface.co/datasets/morteza20/mteb_leaderboard", "tags": ["datasets", "region:us"]}
{"id": "github:jim-schwoebel/awesome_ai_agents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "jim-schwoebel/awesome_ai_agents", "date": "2026-03-28", "createdAt": "2025-01-03", "sourceUpdatedAt": "2026-03-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🤖 A comprehensive list of 1,500+ resources and tools related to AI agents.", "popularity": {"value": 1793, "label": "stars"}, "url": "https://github.com/jim-schwoebel/awesome_ai_agents", "tags": ["agents", "ai-agent"]}
{"id": "github:browser-use/web-ui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "browser-use/web-ui", "date": "2026-05-15", "createdAt": "2025-01-02", "sourceUpdatedAt": "2026-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🖥️ Run AI Agent in your browser.", "popularity": {"value": 16024, "label": "stars"}, "url": "https://github.com/browser-use/web-ui", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:AlgorithmicResearchGroup/s2orc_arxiv", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AlgorithmicResearchGroup/s2orc_arxiv", "date": "2026-04-11", "createdAt": "2024-12-31", "sourceUpdatedAt": "2026-04-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 311989 downloads.", "popularity": {"value": 311989, "label": "downloads"}, "url": "https://huggingface.co/datasets/AlgorithmicResearchGroup/s2orc_arxiv", "tags": ["arxiv", "datasets", "language:en", "modality:text", "nlp", "region:us", "research", "s2orc"]}
{"id": "github:nanobrowser/nanobrowser", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nanobrowser/nanobrowser", "date": "2025-11-24", "createdAt": "2024-12-31", "sourceUpdatedAt": "2025-11-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-Source Chrome extension for AI-powered web automation. Run multi-agent workflows using your own LLM API key. Alternative to OpenAI Operator.", "popularity": {"value": 13079, "label": "stars"}, "url": "https://github.com/nanobrowser/nanobrowser", "tags": ["agents", "ai-tools"]}
{"id": "github:decodingai-magazine/second-brain-ai-assistant-course", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "decodingai-magazine/second-brain-ai-assistant-course", "date": "2026-04-06", "createdAt": "2024-12-30", "sourceUpdatedAt": "2026-04-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.", "popularity": {"value": 2765, "label": "stars"}, "url": "https://github.com/decodingai-magazine/second-brain-ai-assistant-course", "tags": ["agents", "llmops"]}
{"id": "github:tauricresearch/tradingagents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "TauricResearch/TradingAgents", "date": "2026-06-01", "createdAt": "2024-12-28", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "TradingAgents: Multi-Agents LLM Financial Trading Framework", "popularity": {"value": 82720, "label": "stars"}, "url": "https://github.com/TauricResearch/TradingAgents", "tags": ["agents", "llm"]}
{"id": "hf-model:hexgrad/Kokoro-82M", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "hexgrad/Kokoro-82M", "date": "2024-12-26", "createdAt": "2024-12-26", "sourceUpdatedAt": "2024-12-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 13679649 downloads and tags: text-to-speech, en, arxiv:2306.07691, arxiv:2203.02395.", "popularity": {"value": 13679649, "label": "downloads"}, "url": "https://huggingface.co/hexgrad/Kokoro-82M", "tags": ["arxiv:2203.02395", "arxiv:2306.07691", "audio", "base_model:finetune:yl4579/styletts2-ljspeech", "base_model:yl4579/styletts2-ljspeech", "doi:10.57967/hf/4329", "en", "license:apache-2.0"]}
{"id": "github:airweave-ai/airweave", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "airweave-ai/airweave", "date": "2026-06-02", "createdAt": "2024-12-24", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source context retrieval layer for AI agents", "popularity": {"value": 6396, "label": "stars"}, "url": "https://github.com/airweave-ai/airweave", "tags": ["agents", "rag"]}
{"id": "hf-dataset:hf-internal-testing/transformers_circleci_workflow_runs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/transformers_circleci_workflow_runs", "date": "2024-12-20", "createdAt": "2024-12-19", "sourceUpdatedAt": "2024-12-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 254006 downloads.", "popularity": {"value": 254006, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/transformers_circleci_workflow_runs", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:m-a-p/FineFineWeb-sample", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "m-a-p/FineFineWeb-sample", "date": "2024-12-19", "createdAt": "2024-12-18", "sourceUpdatedAt": "2024-12-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55097 downloads.", "popularity": {"value": 55097, "label": "downloads"}, "url": "https://huggingface.co/datasets/m-a-p/FineFineWeb-sample", "tags": ["datasets", "format:json", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:tabular"]}
{"id": "github:arvinlovegood/go-stock", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ArvinLovegood/go-stock", "date": "2026-06-02", "createdAt": "2024-12-17", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🦄🦄🦄AI赋能股票分析：AI加持的股票分析/选股工具。股票行情获取，AI热点资讯分析，AI资金/财务分析，涨跌报警推送。支持A股，港股，美股。支持市场整体/个股情绪分析，AI辅助选股等。数据全部保留在本地。支持DeepSeek，OpenAI， Ollama，LMStudio，AnythingLLM，硅基流动，火山方舟，阿里云百炼等平台或模型。", "popularity": {"value": 6031, "label": "stars"}, "url": "https://github.com/ArvinLovegood/go-stock", "tags": ["ai-tools", "ui-demo"]}
{"id": "hf-dataset:trl-lib/documentation-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "trl-lib/documentation-images", "date": "2026-03-11", "createdAt": "2024-12-17", "sourceUpdatedAt": "2026-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81559 downloads.", "popularity": {"value": 81559, "label": "downloads"}, "url": "https://huggingface.co/datasets/trl-lib/documentation-images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "github:neural-maze/ava-whatsapp-agent-course", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "neural-maze/ava-whatsapp-agent-course", "date": "2025-10-20", "createdAt": "2024-12-17", "sourceUpdatedAt": "2025-10-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Meet Ava, the WhatsApp Agent", "popularity": {"value": 1664, "label": "stars"}, "url": "https://github.com/neural-maze/ava-whatsapp-agent-course", "tags": ["agents", "vector-database"]}
{"id": "hf-dataset:m-a-p/FineFineWeb", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "m-a-p/FineFineWeb", "date": "2024-12-19", "createdAt": "2024-12-14", "sourceUpdatedAt": "2024-12-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 674074 downloads.", "popularity": {"value": 674074, "label": "downloads"}, "url": "https://huggingface.co/datasets/m-a-p/FineFineWeb", "tags": ["datasets", "language:en", "license:apache-2.0", "modality:tabular", "modality:text", "region:us", "size_categories:1b<n<10b", "task_categories:text-classification"]}
{"id": "hf-dataset:ReadyAi/organic_query_results_dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ReadyAi/organic_query_results_dataset", "date": "2025-09-29", "createdAt": "2024-12-13", "sourceUpdatedAt": "2025-09-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66348 downloads.", "popularity": {"value": 66348, "label": "downloads"}, "url": "https://huggingface.co/datasets/ReadyAi/organic_query_results_dataset", "tags": ["datasets", "region:us"]}
{"id": "github:foundationvision/liquid", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "FoundationVision/Liquid", "date": "2026-06-01", "createdAt": "2024-12-12", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "(Accepted by IJCV) Liquid: Language Models are Scalable and Unified Multi-modal Generators", "popularity": {"value": 644, "label": "stars"}, "url": "https://github.com/FoundationVision/Liquid", "tags": ["text-to-image", "tools"]}
{"id": "github:bessouat40/raglight", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Bessouat40/RAGLight", "date": "2026-03-24", "createdAt": "2024-12-12", "sourceUpdatedAt": "2026-03-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.", "popularity": {"value": 664, "label": "stars"}, "url": "https://github.com/Bessouat40/RAGLight", "tags": ["rag", "vector-database"]}
{"id": "github:business-science/ai-data-science-team", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "business-science/ai-data-science-team", "date": "2026-01-28", "createdAt": "2024-12-11", "sourceUpdatedAt": "2026-01-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An AI-powered data science team of agents to help you perform common data science tasks 10X faster.", "popularity": {"value": 5265, "label": "stars"}, "url": "https://github.com/business-science/ai-data-science-team", "tags": ["agents", "generative-ai"]}
{"id": "github:crestalnetwork/intentkit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "crestalnetwork/intentkit", "date": "2026-06-01", "createdAt": "2024-12-09", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.", "popularity": {"value": 6498, "label": "stars"}, "url": "https://github.com/crestalnetwork/intentkit", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:SWE-Gym/SWE-Gym", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SWE-Gym/SWE-Gym", "date": "2025-05-10", "createdAt": "2024-12-09", "sourceUpdatedAt": "2025-05-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 106444 downloads.", "popularity": {"value": 106444, "label": "downloads"}, "url": "https://huggingface.co/datasets/SWE-Gym/SWE-Gym", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit", "modality:text"]}
{"id": "hf-dataset:HuggingFaceFW/fineweb-2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/fineweb-2", "date": "2025-10-27", "createdAt": "2024-12-05", "sourceUpdatedAt": "2025-10-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62097 downloads.", "popularity": {"value": 62097, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/fineweb-2", "tags": ["arxiv:2109.07445", "arxiv:2406.17557", "arxiv:2506.20920", "datasets", "doi:10.57967/hf/3744", "language:aai", "language:aak", "language:aau"]}
{"id": "github:lmnr-ai/index", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lmnr-ai/index", "date": "2025-06-09", "createdAt": "2024-11-30", "sourceUpdatedAt": "2025-06-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The SOTA Open-Source Browser Agent for autonomously performing complex tasks on the web", "popularity": {"value": 2349, "label": "stars"}, "url": "https://github.com/lmnr-ai/index", "tags": ["agents", "ai-agent"]}
{"id": "github:foundationvision/infinity", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "FoundationVision/Infinity", "date": "2026-04-16", "createdAt": "2024-11-29", "sourceUpdatedAt": "2026-04-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis", "popularity": {"value": 1570, "label": "stars"}, "url": "https://github.com/FoundationVision/Infinity", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:defeatbeta/yahoo-finance-data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "defeatbeta/yahoo-finance-data", "date": "2026-06-03", "createdAt": "2024-11-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 106396 downloads.", "popularity": {"value": 106396, "label": "downloads"}, "url": "https://huggingface.co/datasets/defeatbeta/yahoo-finance-data", "tags": ["datasets", "earnings-call-transcripts", "finance", "finance-data", "language:en", "license:odc-by", "market-data", "region:us"]}
{"id": "github:microsoft/ai-agents-for-beginners", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "microsoft/ai-agents-for-beginners", "date": "2026-05-25", "createdAt": "2024-11-28", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "12 Lessons to Get Started Building AI Agents", "popularity": {"value": 66395, "label": "stars"}, "url": "https://github.com/microsoft/ai-agents-for-beginners", "tags": ["agents", "generative-ai"]}
{"id": "hf-model:trl-internal-testing/tiny-Qwen2ForCausalLM-2.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "trl-internal-testing/tiny-Qwen2ForCausalLM-2.5", "date": "2024-11-25", "createdAt": "2024-11-25", "sourceUpdatedAt": "2024-11-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5875961 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 5875961, "label": "downloads"}, "url": "https://huggingface.co/trl-internal-testing/tiny-Qwen2ForCausalLM-2.5", "tags": ["conversational", "endpoints_compatible", "qwen2", "safetensors", "small-local", "text-generation", "text-generation-inference", "transformers"]}
{"id": "github:lehduong/onediffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lehduong/OneDiffusion", "date": "2024-12-14", "createdAt": "2024-11-24", "sourceUpdatedAt": "2024-12-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official implementation of OneDiffusion paper (CVPR 2025)", "popularity": {"value": 661, "label": "stars"}, "url": "https://github.com/lehduong/OneDiffusion", "tags": ["text-to-image", "tools"]}
{"id": "github:helixdb/helix-db", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HelixDB/helix-db", "date": "2026-06-03", "createdAt": "2024-11-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "HelixDB is an open-source graph-vector database built from scratch in Rust.", "popularity": {"value": 4658, "label": "stars"}, "url": "https://github.com/HelixDB/helix-db", "tags": ["vector-database", "vector-db"]}
{"id": "hf-dataset:X779/Danbooruwildcards", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "X779/Danbooruwildcards", "date": "2024-11-23", "createdAt": "2024-11-22", "sourceUpdatedAt": "2024-11-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70211 downloads.", "popularity": {"value": 70211, "label": "downloads"}, "url": "https://huggingface.co/datasets/X779/Danbooruwildcards", "tags": ["datasets", "format:text", "language:en", "library:datasets", "library:mlcroissant", "license:other", "modality:text", "region:us"]}
{"id": "github:lightricks/comfyui-ltxvideo", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Lightricks/ComfyUI-LTXVideo", "date": "2026-05-11", "createdAt": "2024-11-21", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LTX-Video Support for ComfyUI", "popularity": {"value": 3729, "label": "stars"}, "url": "https://github.com/Lightricks/ComfyUI-LTXVideo", "tags": ["text-to-image", "video-tools"]}
{"id": "hf-dataset:AI-MO/olympiads", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AI-MO/olympiads", "date": "2025-11-06", "createdAt": "2024-11-21", "sourceUpdatedAt": "2025-11-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 82434 downloads.", "popularity": {"value": 82434, "label": "downloads"}, "url": "https://huggingface.co/datasets/AI-MO/olympiads", "tags": ["datasets", "modality:document", "region:us"]}
{"id": "hf-dataset:HuggingFaceH4/MATH-500", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceH4/MATH-500", "date": "2025-12-15", "createdAt": "2024-11-15", "sourceUpdatedAt": "2025-12-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 162166 downloads.", "popularity": {"value": 162166, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceH4/MATH-500", "tags": ["datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text"]}
{"id": "github:xiaomingx/awesome-qwen-prompt-insight", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "XiaomingX/awesome-qwen-prompt-insight", "date": "2026-02-01", "createdAt": "2024-11-13", "sourceUpdatedAt": "2026-02-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🧠 世界上覆盖最全的优秀Qwen提示语大全，欢迎贡献你的提示词。🧠 The most comprehensive collection of excellent Qwen prompts in the world. Feel free to contribute your own prompts!", "popularity": {"value": 400, "label": "stars"}, "url": "https://github.com/XiaomingX/awesome-qwen-prompt-insight", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:PleIAs/common_corpus", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "PleIAs/common_corpus", "date": "2026-05-06", "createdAt": "2024-11-12", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 147057 downloads.", "popularity": {"value": 147057, "label": "downloads"}, "url": "https://huggingface.co/datasets/PleIAs/common_corpus", "tags": ["arxiv:2410.22587", "datasets", "format:parquet", "language:ar", "language:de", "language:en", "language:es", "language:fr"]}
{"id": "hf-dataset:Salesforce/GiftEvalPretrain", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Salesforce/GiftEvalPretrain", "date": "2025-01-21", "createdAt": "2024-11-07", "sourceUpdatedAt": "2025-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 282960 downloads.", "popularity": {"value": 282960, "label": "downloads"}, "url": "https://huggingface.co/datasets/Salesforce/GiftEvalPretrain", "tags": ["arxiv:2410.10393", "benchmark", "datasets", "forecasting", "gifteval", "license:apache-2.0", "modality:timeseries", "region:us"]}
{"id": "github:nvidia/kvpress", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NVIDIA/kvpress", "date": "2026-06-03", "createdAt": "2024-11-06", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LLM KV cache compression made easy", "popularity": {"value": 1102, "label": "stars"}, "url": "https://github.com/NVIDIA/kvpress", "tags": ["inference"]}
{"id": "github:steel-dev/steel-browser", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "steel-dev/steel-browser", "date": "2026-06-03", "createdAt": "2024-11-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔥 Open Source Browser API for AI Agents & Apps. Steel Browser is a batteries-included browser sandbox that lets you automate the web without worrying about infrastructure.", "popularity": {"value": 7114, "label": "stars"}, "url": "https://github.com/steel-dev/steel-browser", "tags": ["agents", "ai-tools"]}
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{"id": "hf-dataset:ailsntua/Chordonomicon", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ailsntua/Chordonomicon", "date": "2025-05-15", "createdAt": "2024-10-29", "sourceUpdatedAt": "2025-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 107671 downloads.", "popularity": {"value": 107671, "label": "downloads"}, "url": "https://huggingface.co/datasets/ailsntua/Chordonomicon", "tags": ["arxiv:2410.22046", "datasets", "format:csv", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:cc-by-nc-4.0"]}
{"id": "hf-dataset:wyu1/Leopard-Instruct", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "wyu1/Leopard-Instruct", "date": "2024-11-08", "createdAt": "2024-10-29", "sourceUpdatedAt": "2024-11-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 105504 downloads.", "popularity": {"value": 105504, "label": "downloads"}, "url": "https://huggingface.co/datasets/wyu1/Leopard-Instruct", "tags": ["arxiv:2410.01744", "datasets", "format:parquet", "instruction-following", "language:en", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-model:stabilityai/stable-diffusion-3.5-medium", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "stabilityai/stable-diffusion-3.5-medium", "date": "2024-10-29", "createdAt": "2024-10-29", "sourceUpdatedAt": "2024-10-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 324534 downloads and tags: diffusers, safetensors, text-to-image, stable-diffusion.", "popularity": {"value": 324534, "label": "downloads"}, "url": "https://huggingface.co/stabilityai/stable-diffusion-3.5-medium", "tags": ["arxiv:2403.03206", "diffusers", "en", "image-generation", "license:other", "region:us", "safetensors", "stable-diffusion"]}
{"id": "github:plurai-ai/intellagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "plurai-ai/intellagent", "date": "2026-05-15", "createdAt": "2024-10-28", "sourceUpdatedAt": "2026-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A framework for comprehensive diagnosis and optimization of agents using simulated, realistic synthetic interactions", "popularity": {"value": 1229, "label": "stars"}, "url": "https://github.com/plurai-ai/intellagent", "tags": ["agents", "llmops"]}
{"id": "hf-model:ai4bharat/indic-parler-tts", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "ai4bharat/indic-parler-tts", "date": "2024-10-28", "createdAt": "2024-10-28", "sourceUpdatedAt": "2024-10-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 882066 downloads and tags: transformers, safetensors, parler_tts, text-generation.", "popularity": {"value": 882066, "label": "downloads"}, "url": "https://huggingface.co/ai4bharat/indic-parler-tts", "tags": ["annotation", "as", "audio", "en", "parler_tts", "safetensors", "text-generation", "text-to-speech"]}
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{"id": "github:scalingintelligence/kernelbench", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ScalingIntelligence/KernelBench", "date": "2026-03-24", "createdAt": "2024-10-25", "sourceUpdatedAt": "2026-03-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "KernelBench: Can LLMs Write GPU Kernels? - Benchmark + Toolkit with Torch -> CUDA (+ more DSLs)", "popularity": {"value": 1038, "label": "stars"}, "url": "https://github.com/ScalingIntelligence/KernelBench", "tags": ["evaluation"]}
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{"id": "github:hao-ai-lab/fastvideo", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "hao-ai-lab/FastVideo", "date": "2026-06-02", "createdAt": "2024-10-24", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A unified inference and post-training framework for accelerated video generation.", "popularity": {"value": 3675, "label": "stars"}, "url": "https://github.com/hao-ai-lab/FastVideo", "tags": ["inference", "video-tools"]}
{"id": "github:agibottech/agibot_x1_infer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AgibotTech/agibot_x1_infer", "date": "2025-04-03", "createdAt": "2024-10-23", "sourceUpdatedAt": "2025-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The inference module for AgiBot X1.", "popularity": {"value": 1816, "label": "stars"}, "url": "https://github.com/AgibotTech/agibot_x1_infer", "tags": ["inference"]}
{"id": "github:integuru-ai/integuru", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Integuru-AI/Integuru", "date": "2026-05-26", "createdAt": "2024-10-22", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The first AI agent that builds permissionless integrations through reverse engineering platforms' internal APIs.", "popularity": {"value": 4608, "label": "stars"}, "url": "https://github.com/Integuru-AI/Integuru", "tags": ["agents", "ai-agent"]}
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{"id": "github:patchy631/ai-engineering-hub", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "patchy631/ai-engineering-hub", "date": "2026-05-21", "createdAt": "2024-10-21", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "In-depth tutorials on LLMs, RAGs and real-world AI agent applications.", "popularity": {"value": 35514, "label": "stars"}, "url": "https://github.com/patchy631/ai-engineering-hub", "tags": ["agents", "rag"]}
{"id": "hf-dataset:HPLT/HPLT2.0_cleaned", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HPLT/HPLT2.0_cleaned", "date": "2025-11-13", "createdAt": "2024-10-19", "sourceUpdatedAt": "2025-11-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52779 downloads.", "popularity": {"value": 52779, "label": "downloads"}, "url": "https://huggingface.co/datasets/HPLT/HPLT2.0_cleaned", "tags": ["arxiv:2503.10267", "datasets", "language:ace", "language:af", "language:als", "language:am", "language:ar", "language:as"]}
{"id": "github:adaline/gateway", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "adaline/gateway", "date": "2026-05-28", "createdAt": "2024-10-15", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for calling more than 200+ LLMs.", "popularity": {"value": 593, "label": "stars"}, "url": "https://github.com/adaline/gateway", "tags": ["llmops", "tools"]}
{"id": "hf-dataset:laion/hamburg_curricula_2024", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "laion/hamburg_curricula_2024", "date": "2024-10-16", "createdAt": "2024-10-15", "sourceUpdatedAt": "2024-10-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 82902 downloads.", "popularity": {"value": 82902, "label": "downloads"}, "url": "https://huggingface.co/datasets/laion/hamburg_curricula_2024", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "github:nirdiamant/prompt_engineering", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NirDiamant/Prompt_Engineering", "date": "2026-06-03", "createdAt": "2024-10-10", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.", "popularity": {"value": 7559, "label": "stars"}, "url": "https://github.com/NirDiamant/Prompt_Engineering", "tags": ["generative-ai", "rag"]}
{"id": "github:huggingface/evaluation-guidebook", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "huggingface/evaluation-guidebook", "date": "2025-12-03", "createdAt": "2024-10-09", "sourceUpdatedAt": "2025-12-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!", "popularity": {"value": 2113, "label": "stars"}, "url": "https://github.com/huggingface/evaluation-guidebook", "tags": ["evaluation"]}
{"id": "hf-model:SWivid/F5-TTS", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "SWivid/F5-TTS", "date": "2024-10-07", "createdAt": "2024-10-07", "sourceUpdatedAt": "2024-10-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 622055 downloads and tags: f5-tts, text-to-speech, dataset:amphion/Emilia-Dataset, arxiv:2410.06885.", "popularity": {"value": 622055, "label": "downloads"}, "url": "https://huggingface.co/SWivid/F5-TTS", "tags": ["arxiv:2410.06885", "audio", "dataset:amphion/emilia-dataset", "f5-tts", "license:cc-by-nc-4.0", "region:us", "text-to-speech"]}
{"id": "hf-dataset:LLM360/TxT360", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "LLM360/TxT360", "date": "2025-05-26", "createdAt": "2024-10-03", "sourceUpdatedAt": "2025-05-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 99584 downloads.", "popularity": {"value": 99584, "label": "downloads"}, "url": "https://huggingface.co/datasets/LLM360/TxT360", "tags": ["datasets", "language:en", "license:odc-by", "region:us", "size_categories:n>1t", "task_categories:text-generation"]}
{"id": "github:hkuds/lightrag", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HKUDS/LightRAG", "date": "2026-06-04", "createdAt": "2024-10-02", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[EMNLP2025] \"LightRAG: Simple and Fast Retrieval-Augmented Generation\"", "popularity": {"value": 36141, "label": "stars"}, "url": "https://github.com/HKUDS/LightRAG", "tags": ["llm", "rag"]}
{"id": "hf-model:openai/whisper-large-v3-turbo", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/whisper-large-v3-turbo", "date": "2024-10-01", "createdAt": "2024-10-01", "sourceUpdatedAt": "2024-10-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 8613083 downloads and tags: transformers, safetensors, whisper, automatic-speech-recognition.", "popularity": {"value": 8613083, "label": "downloads"}, "url": "https://huggingface.co/openai/whisper-large-v3-turbo", "tags": ["audio", "automatic-speech-recognition", "de", "en", "safetensors", "transformers", "whisper", "zh"]}
{"id": "hf-dataset:ziyjiang/MMEB_Test_Instruct", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ziyjiang/MMEB_Test_Instruct", "date": "2024-10-01", "createdAt": "2024-09-30", "sourceUpdatedAt": "2024-10-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 76146 downloads.", "popularity": {"value": 76146, "label": "downloads"}, "url": "https://huggingface.co/datasets/ziyjiang/MMEB_Test_Instruct", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:tropos-labs/eigen-face-dataset-256", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tropos-labs/eigen-face-dataset-256", "date": "2025-02-19", "createdAt": "2024-09-29", "sourceUpdatedAt": "2025-02-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58061 downloads.", "popularity": {"value": 58061, "label": "downloads"}, "url": "https://huggingface.co/datasets/tropos-labs/eigen-face-dataset-256", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:nvidia/OpenMathInstruct-2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nvidia/OpenMathInstruct-2", "date": "2024-11-25", "createdAt": "2024-09-28", "sourceUpdatedAt": "2024-11-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67230 downloads.", "popularity": {"value": 67230, "label": "downloads"}, "url": "https://huggingface.co/datasets/nvidia/OpenMathInstruct-2", "tags": ["arxiv:2410.01560", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "github:dynamiq-ai/dynamiq", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dynamiq-ai/dynamiq", "date": "2026-06-03", "createdAt": "2024-09-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Dynamiq is an orchestration framework for agentic AI and LLM applications", "popularity": {"value": 1052, "label": "stars"}, "url": "https://github.com/dynamiq-ai/dynamiq", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:SilvioGiancola/TrackingNet", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SilvioGiancola/TrackingNet", "date": "2024-11-06", "createdAt": "2024-09-26", "sourceUpdatedAt": "2024-11-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58687 downloads.", "popularity": {"value": 58687, "label": "downloads"}, "url": "https://huggingface.co/datasets/SilvioGiancola/TrackingNet", "tags": ["arxiv:1803.10794", "datasets", "license:gpl-3.0", "motion", "propagation", "region:us", "size_categories:10k<n<100k", "tracking"]}
{"id": "github:pyspur-dev/pyspur", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "PySpur-Dev/pyspur", "date": "2026-05-25", "createdAt": "2024-09-23", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A visual playground for agentic workflows: Iterate over your agents 10x faster", "popularity": {"value": 5732, "label": "stars"}, "url": "https://github.com/PySpur-Dev/pyspur", "tags": ["agents", "rag"]}
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{"id": "github:azure-samples/aisearch-openai-rag-audio", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Azure-Samples/aisearch-openai-rag-audio", "date": "2025-11-19", "createdAt": "2024-09-19", "sourceUpdatedAt": "2025-11-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A simple example implementation of the VoiceRAG pattern to power interactive voice generative AI experiences using RAG with Azure AI Search and Azure OpenAI's gpt-4o-realtime-preview model.", "popularity": {"value": 556, "label": "stars"}, "url": "https://github.com/Azure-Samples/aisearch-openai-rag-audio", "tags": ["rag", "vector-database"]}
{"id": "hf-model:meta-llama/Llama-3.2-1B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "meta-llama/Llama-3.2-1B-Instruct", "date": "2024-09-18", "createdAt": "2024-09-18", "sourceUpdatedAt": "2024-09-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 8363587 downloads and tags: transformers, safetensors, llama, text-generation.", "popularity": {"value": 8363587, "label": "downloads"}, "url": "https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct", "tags": ["facebook", "llama", "llama-3", "llm", "meta", "pytorch", "safetensors", "text-generation"]}
{"id": "github:zml/zml", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zml/zml", "date": "2026-06-03", "createdAt": "2024-09-17", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild", "popularity": {"value": 3581, "label": "stars"}, "url": "https://github.com/zml/zml", "tags": ["inference"]}
{"id": "hf-model:Qwen/Qwen2.5-1.5B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2.5-1.5B-Instruct", "date": "2024-09-17", "createdAt": "2024-09-17", "sourceUpdatedAt": "2024-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 14563243 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 14563243, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct", "tags": ["arxiv:2407.10671", "chat", "conversational", "en", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen2.5-3B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2.5-3B-Instruct", "date": "2024-09-17", "createdAt": "2024-09-17", "sourceUpdatedAt": "2024-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 13976297 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 13976297, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2.5-3B-Instruct", "tags": ["arxiv:2407.10671", "chat", "conversational", "en", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen2.5-7B-Instruct-AWQ", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2.5-7B-Instruct-AWQ", "date": "2024-09-17", "createdAt": "2024-09-17", "sourceUpdatedAt": "2024-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2827937 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 2827937, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-AWQ", "tags": ["arxiv:2309.00071", "chat", "conversational", "en", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "hf-dataset:baber/multilingual_mmlu", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "baber/multilingual_mmlu", "date": "2024-09-17", "createdAt": "2024-09-17", "sourceUpdatedAt": "2024-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56252 downloads.", "popularity": {"value": 56252, "label": "downloads"}, "url": "https://huggingface.co/datasets/baber/multilingual_mmlu", "tags": ["datasets", "license:mit", "modality:text", "region:us", "size_categories:100k<n<1m", "task_categories:text-generation"]}
{"id": "hf-model:Qwen/Qwen2.5-7B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2.5-7B-Instruct", "date": "2024-09-16", "createdAt": "2024-09-16", "sourceUpdatedAt": "2024-09-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 12555080 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 12555080, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2.5-7B-Instruct", "tags": ["arxiv:2309.00071", "chat", "conversational", "en", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "hf-model:Qwen/Qwen2.5-0.5B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2.5-0.5B-Instruct", "date": "2024-09-16", "createdAt": "2024-09-16", "sourceUpdatedAt": "2024-09-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4199935 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 4199935, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct", "tags": ["arxiv:2407.10671", "chat", "conversational", "en", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "hf-dataset:Zyphra/Zyda-2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Zyphra/Zyda-2", "date": "2025-08-06", "createdAt": "2024-09-13", "sourceUpdatedAt": "2025-08-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 231069 downloads.", "popularity": {"value": 231069, "label": "downloads"}, "url": "https://huggingface.co/datasets/Zyphra/Zyda-2", "tags": ["datasets", "language:en", "license:odc-by", "region:us", "size_categories:n>1t", "task_categories:text-generation"]}
{"id": "hf-dataset:trl-internal-testing/zen", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "trl-internal-testing/zen", "date": "2024-11-26", "createdAt": "2024-09-13", "sourceUpdatedAt": "2024-11-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67613 downloads.", "popularity": {"value": 67613, "label": "downloads"}, "url": "https://huggingface.co/datasets/trl-internal-testing/zen", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:japanese-asr/whisper_transcriptions.reazon_speech_all.wer_10.0.vectorized", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "japanese-asr/whisper_transcriptions.reazon_speech_all.wer_10.0.vectorized", "date": "2024-09-17", "createdAt": "2024-09-12", "sourceUpdatedAt": "2024-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 178005 downloads.", "popularity": {"value": 178005, "label": "downloads"}, "url": "https://huggingface.co/datasets/japanese-asr/whisper_transcriptions.reazon_speech_all.wer_10.0.vectorized", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "region:us", "size_categories:1m<n<10m"]}
{"id": "hf-model:kyutai/mimi", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "kyutai/mimi", "date": "2024-09-10", "createdAt": "2024-09-10", "sourceUpdatedAt": "2024-09-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2359004 downloads and tags: transformers, safetensors, mimi, feature-extraction.", "popularity": {"value": 2359004, "label": "downloads"}, "url": "https://huggingface.co/kyutai/mimi", "tags": ["audio", "embeddings", "endpoints_compatible", "feature-extraction", "license:cc-by-4.0", "mimi", "region:us", "safetensors"]}
{"id": "github:nirdiamant/genai_agents", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NirDiamant/GenAI_Agents", "date": "2026-06-03", "createdAt": "2024-09-09", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.", "popularity": {"value": 22360, "label": "stars"}, "url": "https://github.com/NirDiamant/GenAI_Agents", "tags": ["agents", "llm"]}
{"id": "hf-dataset:japanese-asr/whisper_transcriptions.reazon_speech_all", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "japanese-asr/whisper_transcriptions.reazon_speech_all", "date": "2024-09-14", "createdAt": "2024-09-07", "sourceUpdatedAt": "2024-09-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 433012 downloads.", "popularity": {"value": 433012, "label": "downloads"}, "url": "https://huggingface.co/datasets/japanese-asr/whisper_transcriptions.reazon_speech_all", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:audio", "modality:text"]}
{"id": "hf-model:jinaai/jina-embeddings-v3", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jinaai/jina-embeddings-v3", "date": "2024-09-05", "createdAt": "2024-09-05", "sourceUpdatedAt": "2024-09-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3964415 downloads and tags: transformers, pytorch, onnx, safetensors.", "popularity": {"value": 3964415, "label": "downloads"}, "url": "https://huggingface.co/jinaai/jina-embeddings-v3", "tags": ["embeddings", "feature-extraction", "mteb", "onnx", "pytorch", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "github:supervc-stack/vectorchord", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "supervc-stack/VectorChord", "date": "2026-04-30", "createdAt": "2024-09-03", "sourceUpdatedAt": "2026-04-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.", "popularity": {"value": 1691, "label": "stars"}, "url": "https://github.com/supervc-stack/VectorChord", "tags": ["tools", "vector-database"]}
{"id": "github:deepsense-ai/ragbits", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "deepsense-ai/ragbits", "date": "2026-05-18", "createdAt": "2024-09-02", "sourceUpdatedAt": "2026-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Building blocks for rapid development of GenAI applications", "popularity": {"value": 1645, "label": "stars"}, "url": "https://github.com/deepsense-ai/ragbits", "tags": ["evaluation", "rag"]}
{"id": "hf-model:stable-diffusion-v1-5/stable-diffusion-v1-5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "stable-diffusion-v1-5/stable-diffusion-v1-5", "date": "2024-08-30", "createdAt": "2024-08-30", "sourceUpdatedAt": "2024-08-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1806365 downloads and tags: diffusers, safetensors, stable-diffusion, stable-diffusion-diffusers.", "popularity": {"value": 1806365, "label": "downloads"}, "url": "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5", "tags": ["arxiv:2103.00020", "arxiv:2112.10752", "arxiv:2207.12598", "diffusers", "image-generation", "safetensors", "stable-diffusion", "stable-diffusion-diffusers"]}
{"id": "hf-dataset:anchovy/salesforce-lotsa_data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "anchovy/salesforce-lotsa_data", "date": "2024-08-30", "createdAt": "2024-08-30", "sourceUpdatedAt": "2024-08-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 57088 downloads.", "popularity": {"value": 57088, "label": "downloads"}, "url": "https://huggingface.co/datasets/anchovy/salesforce-lotsa_data", "tags": ["arxiv:2402.02592", "datasets", "license:apache-2.0", "region:us"]}
{"id": "github:lmnr-ai/lmnr", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lmnr-ai/lmnr", "date": "2026-06-03", "createdAt": "2024-08-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Laminar - open-source observability platform purpose-built for AI agents. YC S24.", "popularity": {"value": 2974, "label": "stars"}, "url": "https://github.com/lmnr-ai/lmnr", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:benjamin-paine/freesound-laion-640k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "benjamin-paine/freesound-laion-640k", "date": "2024-09-07", "createdAt": "2024-08-29", "sourceUpdatedAt": "2024-09-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 115148 downloads.", "popularity": {"value": 115148, "label": "downloads"}, "url": "https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k", "tags": ["datasets", "format:parquet", "freesound", "freesound.org", "laion", "laion-audio", "library:dask", "library:datasets"]}
{"id": "github:raga-ai-hub/ragaai-catalyst", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "raga-ai-hub/RagaAI-Catalyst", "date": "2026-02-11", "createdAt": "2024-08-26", "sourceUpdatedAt": "2026-02-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view", "popularity": {"value": 16170, "label": "stars"}, "url": "https://github.com/raga-ai-hub/RagaAI-Catalyst", "tags": ["agents", "llmops"]}
{"id": "github:i-am-bee/beeai-framework", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "i-am-bee/beeai-framework", "date": "2026-05-28", "createdAt": "2024-08-23", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build production-ready AI agents in both Python and Typescript.", "popularity": {"value": 3278, "label": "stars"}, "url": "https://github.com/i-am-bee/beeai-framework", "tags": ["agents", "ai-agent"]}
{"id": "github:efeslab/nanoflow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "efeslab/Nanoflow", "date": "2026-03-29", "createdAt": "2024-08-19", "sourceUpdatedAt": "2026-03-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A throughput-oriented high-performance serving framework for LLMs", "popularity": {"value": 962, "label": "stars"}, "url": "https://github.com/efeslab/Nanoflow", "tags": ["inference"]}
{"id": "hf-dataset:princeton-nlp/SWE-bench_Verified", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "princeton-nlp/SWE-bench_Verified", "date": "2025-02-18", "createdAt": "2024-08-13", "sourceUpdatedAt": "2025-02-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 916713 downloads.", "popularity": {"value": 916713, "label": "downloads"}, "url": "https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:potpie-ai/potpie", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "potpie-ai/potpie", "date": "2026-06-03", "createdAt": "2024-08-12", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Spec-driven development for large codebases", "popularity": {"value": 5413, "label": "stars"}, "url": "https://github.com/potpie-ai/potpie", "tags": ["rag"]}
{"id": "github:getzep/graphiti", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "getzep/graphiti", "date": "2026-05-21", "createdAt": "2024-08-08", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build Real-Time Knowledge Graphs for AI Agents", "popularity": {"value": 26971, "label": "stars"}, "url": "https://github.com/getzep/graphiti", "tags": ["agents", "rag"]}
{"id": "hf-dataset:mesolitica/fineweb-filter-malaysian-context", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mesolitica/fineweb-filter-malaysian-context", "date": "2024-08-13", "createdAt": "2024-08-07", "sourceUpdatedAt": "2024-08-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54027 downloads.", "popularity": {"value": 54027, "label": "downloads"}, "url": "https://huggingface.co/datasets/mesolitica/fineweb-filter-malaysian-context", "tags": ["datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:tabular"]}
{"id": "github:mastra-ai/mastra", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mastra-ai/mastra", "date": "2026-06-04", "createdAt": "2024-08-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.", "popularity": {"value": 24729, "label": "stars"}, "url": "https://github.com/mastra-ai/mastra", "tags": ["agents", "llm"]}
{"id": "github:codexu/note-gen", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "codexu/note-gen", "date": "2026-06-03", "createdAt": "2024-08-06", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A cross-platform Markdown AI note-taking software.", "popularity": {"value": 12026, "label": "stars"}, "url": "https://github.com/codexu/note-gen", "tags": ["rag"]}
{"id": "github:luhengshiwo/llmforeverybody", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "luhengshiwo/LLMForEverybody", "date": "2026-05-31", "createdAt": "2024-08-05", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "每个人都能看懂的大模型知识分享，LLMs春/秋招大模型面试前必看，让你和面试官侃侃而谈", "popularity": {"value": 6653, "label": "stars"}, "url": "https://github.com/luhengshiwo/LLMForEverybody", "tags": ["rag"]}
{"id": "github:sayakpaul/diffusers-torchao", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "sayakpaul/diffusers-torchao", "date": "2026-01-08", "createdAt": "2024-08-05", "sourceUpdatedAt": "2026-01-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "End-to-end recipes for optimizing diffusion models with torchao and diffusers (inference and FP8 training).", "popularity": {"value": 396, "label": "stars"}, "url": "https://github.com/sayakpaul/diffusers-torchao", "tags": ["inference", "text-to-image"]}
{"id": "hf-dataset:applied-ai-018/pretraining_v1-omega_books", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "applied-ai-018/pretraining_v1-omega_books", "date": "2024-08-05", "createdAt": "2024-07-31", "sourceUpdatedAt": "2024-08-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 159100 downloads.", "popularity": {"value": 159100, "label": "downloads"}, "url": "https://huggingface.co/datasets/applied-ai-018/pretraining_v1-omega_books", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:tabular", "modality:text"]}
{"id": "hf-dataset:applied-ai-018/pretraining_v1-omega", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "applied-ai-018/pretraining_v1-omega", "date": "2024-08-02", "createdAt": "2024-07-31", "sourceUpdatedAt": "2024-08-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 117980 downloads.", "popularity": {"value": 117980, "label": "downloads"}, "url": "https://huggingface.co/datasets/applied-ai-018/pretraining_v1-omega", "tags": ["datasets", "region:us"]}
{"id": "hf-model:black-forest-labs/FLUX.1-dev", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "black-forest-labs/FLUX.1-dev", "date": "2024-07-31", "createdAt": "2024-07-31", "sourceUpdatedAt": "2024-07-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 706361 downloads and tags: diffusers, safetensors, text-to-image, image-generation.", "popularity": {"value": 706361, "label": "downloads"}, "url": "https://huggingface.co/black-forest-labs/FLUX.1-dev", "tags": ["diffusers", "en", "endpoints_compatible", "flux", "image-generation", "license:other", "safetensors", "text-to-image"]}
{"id": "hf-model:black-forest-labs/FLUX.1-schnell", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "black-forest-labs/FLUX.1-schnell", "date": "2024-07-31", "createdAt": "2024-07-31", "sourceUpdatedAt": "2024-07-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 467532 downloads and tags: diffusers, safetensors, text-to-image, image-generation.", "popularity": {"value": 467532, "label": "downloads"}, "url": "https://huggingface.co/black-forest-labs/FLUX.1-schnell", "tags": ["diffusers", "en", "endpoints_compatible", "flux", "image-generation", "license:apache-2.0", "safetensors", "text-to-image"]}
{"id": "github:modsetter/surfsense", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MODSetter/SurfSense", "date": "2026-06-04", "createdAt": "2024-07-30", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An open source, privacy focused alternative to NotebookLM for teams with no data limits. Join our Discord: https://discord.gg/ejRNvftDp9", "popularity": {"value": 14396, "label": "stars"}, "url": "https://github.com/MODSetter/SurfSense", "tags": ["rag"]}
{"id": "hf-model:BAAI/bge-multilingual-gemma2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-multilingual-gemma2", "date": "2024-07-25", "createdAt": "2024-07-25", "sourceUpdatedAt": "2024-07-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1412047 downloads and tags: sentence-transformers, safetensors, gemma2, feature-extraction.", "popularity": {"value": 1412047, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-multilingual-gemma2", "tags": ["arxiv:2402.03216", "embeddings", "feature-extraction", "gemma2", "mteb", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "github:kiln-ai/kiln", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Kiln-AI/Kiln", "date": "2026-06-03", "createdAt": "2024-07-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.", "popularity": {"value": 4860, "label": "stars"}, "url": "https://github.com/Kiln-AI/Kiln", "tags": ["agents", "evaluation"]}
{"id": "github:2fastlabs/agent-squad", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "2FastLabs/agent-squad", "date": "2026-05-29", "createdAt": "2024-07-23", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Flexible and powerful framework for managing multiple AI agents and handling complex conversations", "popularity": {"value": 7645, "label": "stars"}, "url": "https://github.com/2FastLabs/agent-squad", "tags": ["agents", "generative-ai"]}
{"id": "github:intellabs/rag-fit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "IntelLabs/RAG-FiT", "date": "2025-12-16", "createdAt": "2024-07-23", "sourceUpdatedAt": "2025-12-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Framework for enhancing LLMs for RAG tasks using fine-tuning.", "popularity": {"value": 770, "label": "stars"}, "url": "https://github.com/IntelLabs/RAG-FiT", "tags": ["evaluation", "rag"]}
{"id": "hf-dataset:airtrain-ai/fineweb-edu-fortified", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "airtrain-ai/fineweb-edu-fortified", "date": "2024-08-08", "createdAt": "2024-07-22", "sourceUpdatedAt": "2024-08-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 429529 downloads.", "popularity": {"value": 429529, "label": "downloads"}, "url": "https://huggingface.co/datasets/airtrain-ai/fineweb-edu-fortified", "tags": ["arxiv:2109.07445", "arxiv:2406.17557", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:fixie-ai/common_voice_17_0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fixie-ai/common_voice_17_0", "date": "2025-01-17", "createdAt": "2024-07-21", "sourceUpdatedAt": "2025-01-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 137464 downloads.", "popularity": {"value": 137464, "label": "downloads"}, "url": "https://huggingface.co/datasets/fixie-ai/common_voice_17_0", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:audio", "modality:text"]}
{"id": "hf-dataset:mlfoundations/MINT-1T-HTML", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/MINT-1T-HTML", "date": "2024-09-21", "createdAt": "2024-07-21", "sourceUpdatedAt": "2024-09-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 224784 downloads.", "popularity": {"value": 224784, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/MINT-1T-HTML", "tags": ["arxiv:2406.11271", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-model:meta-llama/Llama-3.1-8B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "meta-llama/Llama-3.1-8B-Instruct", "date": "2024-07-18", "createdAt": "2024-07-18", "sourceUpdatedAt": "2024-07-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 10943455 downloads and tags: transformers, safetensors, llama, text-generation.", "popularity": {"value": 10943455, "label": "downloads"}, "url": "https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct", "tags": ["facebook", "llama", "llama-3", "llm", "meta", "pytorch", "safetensors", "text-generation"]}
{"id": "github:ashbuilds/payload-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ashbuilds/payload-ai", "date": "2026-05-21", "createdAt": "2024-07-17", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Plugin is a powerful extension for the Payload CMS, integrating advanced AI capabilities to enhance content creation and management.", "popularity": {"value": 507, "label": "stars"}, "url": "https://github.com/ashbuilds/payload-ai", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill", "date": "2024-07-17", "createdAt": "2024-07-17", "sourceUpdatedAt": "2024-07-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 735771 downloads and tags: sentence-transformers, pytorch, safetensors, distilbert.", "popularity": {"value": 735771, "label": "downloads"}, "url": "https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill", "tags": ["coding", "distilbert", "fill-mask", "learned sparse", "opensearch", "pytorch", "safetensors", "sentence-transformers"]}
{"id": "github:tensorzero/tensorzero", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "tensorzero/tensorzero", "date": "2026-06-03", "createdAt": "2024-07-16", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.", "popularity": {"value": 11430, "label": "stars"}, "url": "https://github.com/tensorzero/tensorzero", "tags": ["evaluation", "llmops"]}
{"id": "hf-dataset:fixie-ai/covost2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fixie-ai/covost2", "date": "2024-08-27", "createdAt": "2024-07-16", "sourceUpdatedAt": "2024-08-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 247944 downloads.", "popularity": {"value": 247944, "label": "downloads"}, "url": "https://huggingface.co/datasets/fixie-ai/covost2", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:audio", "modality:text"]}
{"id": "hf-dataset:AI-MO/NuminaMath-CoT", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AI-MO/NuminaMath-CoT", "date": "2024-11-25", "createdAt": "2024-07-15", "sourceUpdatedAt": "2024-11-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58828 downloads.", "popularity": {"value": 58828, "label": "downloads"}, "url": "https://huggingface.co/datasets/AI-MO/NuminaMath-CoT", "tags": ["aimo", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:HuggingFaceTB/smollm-corpus", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceTB/smollm-corpus", "date": "2024-09-06", "createdAt": "2024-07-15", "sourceUpdatedAt": "2024-09-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55239 downloads.", "popularity": {"value": 55239, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus", "tags": ["datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:odc-by"]}
{"id": "hf-dataset:andyvhuynh/NatureMultiView", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "andyvhuynh/NatureMultiView", "date": "2024-07-18", "createdAt": "2024-07-15", "sourceUpdatedAt": "2024-07-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 90483 downloads.", "popularity": {"value": 90483, "label": "downloads"}, "url": "https://huggingface.co/datasets/andyvhuynh/NatureMultiView", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:image", "modality:text"]}
{"id": "github:xuyang-liu16/awesome-generation-acceleration", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "xuyang-liu16/Awesome-Generation-Acceleration", "date": "2025-07-07", "createdAt": "2024-07-14", "sourceUpdatedAt": "2025-07-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📚 Collection of awesome generation acceleration resources.", "popularity": {"value": 399, "label": "stars"}, "url": "https://github.com/xuyang-liu16/Awesome-Generation-Acceleration", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:unslothai/1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "unslothai/1", "date": "2024-07-14", "createdAt": "2024-07-14", "sourceUpdatedAt": "2024-07-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1405996 downloads and tags: transformers, safetensors, llama, feature-extraction.", "popularity": {"value": 1405996, "label": "downloads"}, "url": "https://huggingface.co/unslothai/1", "tags": ["deploy:azure", "embeddings", "endpoints_compatible", "feature-extraction", "llama", "region:us", "safetensors", "transformers"]}
{"id": "github:nirdiamant/rag_techniques", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NirDiamant/RAG_Techniques", "date": "2026-06-03", "createdAt": "2024-07-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.", "popularity": {"value": 27703, "label": "stars"}, "url": "https://github.com/NirDiamant/RAG_Techniques", "tags": ["llm", "rag"]}
{"id": "github:yamadashy/repomix", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "yamadashy/repomix", "date": "2026-06-03", "createdAt": "2024-07-13", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llam...", "popularity": {"value": 25927, "label": "stars"}, "url": "https://github.com/yamadashy/repomix", "tags": ["developer-tools", "llm"]}
{"id": "github:samuraigpt/ai-faceless-video-generator", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SamurAIGPT/AI-Faceless-Video-Generator", "date": "2026-02-06", "createdAt": "2024-07-12", "sourceUpdatedAt": "2026-02-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Generate a video script, voice and a talking face completely with AI", "popularity": {"value": 442, "label": "stars"}, "url": "https://github.com/SamurAIGPT/AI-Faceless-Video-Generator", "tags": ["text-to-image", "video-tools"]}
{"id": "hf-dataset:mlfoundations/MINT-1T-PDF-CC-2023-06", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/MINT-1T-PDF-CC-2023-06", "date": "2024-09-19", "createdAt": "2024-07-12", "sourceUpdatedAt": "2024-09-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55402 downloads.", "popularity": {"value": 55402, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-06", "tags": ["arxiv:2406.11271", "datasets", "language:en", "license:cc-by-4.0", "multimodal", "region:us", "size_categories:100b<n<1t", "task_categories:image-to-text"]}
{"id": "github:trustgraph-ai/trustgraph", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "trustgraph-ai/trustgraph", "date": "2026-06-03", "createdAt": "2024-07-10", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The semantic deployment platform.", "popularity": {"value": 2132, "label": "stars"}, "url": "https://github.com/trustgraph-ai/trustgraph", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:elizaos/eliza", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "elizaOS/eliza", "date": "2026-06-04", "createdAt": "2024-07-09", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open source agentic operating system", "popularity": {"value": 18504, "label": "stars"}, "url": "https://github.com/elizaOS/eliza", "tags": ["agents", "rag"]}
{"id": "github:katanemo/plano", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "katanemo/plano", "date": "2026-06-03", "createdAt": "2024-07-09", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Plano is an AI-native proxy and data plane for agentic apps — with built-in orchestration, safety, observability, and smart LLM routing so you stay focused on your agents core logic.", "popularity": {"value": 6567, "label": "stars"}, "url": "https://github.com/katanemo/plano", "tags": ["agents", "llmops"]}
{"id": "hf-model:unslothai/repeat", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "unslothai/repeat", "date": "2024-07-07", "createdAt": "2024-07-07", "sourceUpdatedAt": "2024-07-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1226093 downloads and tags: transformers, safetensors, llama, feature-extraction.", "popularity": {"value": 1226093, "label": "downloads"}, "url": "https://huggingface.co/unslothai/repeat", "tags": ["embeddings", "endpoints_compatible", "feature-extraction", "llama", "region:us", "safetensors", "transformers"]}
{"id": "hf-dataset:mteb/results", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mteb/results", "date": "2026-05-31", "createdAt": "2024-07-06", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 1504804 downloads.", "popularity": {"value": 1504804, "label": "downloads"}, "url": "https://huggingface.co/datasets/mteb/results", "tags": ["datasets", "region:us"]}
{"id": "github:xerrors/yuxi", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "xerrors/Yuxi", "date": "2026-05-26", "createdAt": "2024-07-05", "sourceUpdatedAt": "2026-05-26", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "结合知识库、知识图谱管理的 多租户 Agent Harness 平台。 An agent harness that integrates a LightRAG knowledge base and knowledge graphs. Build with LangChain + Vue + FastAPI, support DeepAgents、MinerU PDF、Neo4j 、MCP.", "popularity": {"value": 5325, "label": "stars"}, "url": "https://github.com/xerrors/Yuxi", "tags": ["agents", "rag"]}
{"id": "github:cheahjs/free-llm-api-resources", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "cheahjs/free-llm-api-resources", "date": "2026-06-01", "createdAt": "2024-07-04", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A list of free LLM inference resources accessible via API.", "popularity": {"value": 22775, "label": "stars"}, "url": "https://github.com/cheahjs/free-llm-api-resources", "tags": ["inference", "llm"]}
{"id": "github:chaofantao/autoregressive-models-in-vision-survey", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ChaofanTao/Autoregressive-Models-in-Vision-Survey", "date": "2026-05-05", "createdAt": "2024-07-01", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[TMLR 2025🔥] A survey for the autoregressive models in vision.", "popularity": {"value": 797, "label": "stars"}, "url": "https://github.com/ChaofanTao/Autoregressive-Models-in-Vision-Survey", "tags": ["text-to-image", "tools"]}
{"id": "github:open-mmlab/styleshot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "open-mmlab/StyleShot", "date": "2025-06-30", "createdAt": "2024-07-01", "sourceUpdatedAt": "2025-06-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "StyleShot: A SnapShot on Any Style. 一款可以迁移任意风格到任意内容的模型，无需针对图片微调，即能生成高质量的个性风格化图片!", "popularity": {"value": 466, "label": "stars"}, "url": "https://github.com/open-mmlab/StyleShot", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:mlfoundations/dclm-baseline-1.0-parquet", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/dclm-baseline-1.0-parquet", "date": "2024-07-19", "createdAt": "2024-06-30", "sourceUpdatedAt": "2024-07-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 690442 downloads.", "popularity": {"value": 690442, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0-parquet", "tags": ["arxiv:2406.11794", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:mlfoundations/MINT-1T-ArXiv", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/MINT-1T-ArXiv", "date": "2024-09-19", "createdAt": "2024-06-29", "sourceUpdatedAt": "2024-09-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 166824 downloads.", "popularity": {"value": 166824, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/MINT-1T-ArXiv", "tags": ["arxiv:2406.11271", "datasets", "format:webdataset", "language:en", "library:datasets", "library:mlcroissant", "library:webdataset", "license:cc-by-4.0"]}
{"id": "github:handsonllm/hands-on-large-language-models", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HandsOnLLM/Hands-On-Large-Language-Models", "date": "2026-04-24", "createdAt": "2024-06-28", "sourceUpdatedAt": "2026-04-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official code repo for the O'Reilly Book - \"Hands-On Large Language Models\"", "popularity": {"value": 26761, "label": "stars"}, "url": "https://github.com/HandsOnLLM/Hands-On-Large-Language-Models", "tags": ["llm", "tools"]}
{"id": "github:kvcache-ai/mooncake", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "kvcache-ai/Mooncake", "date": "2026-06-04", "createdAt": "2024-06-25", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.", "popularity": {"value": 5501, "label": "stars"}, "url": "https://github.com/kvcache-ai/Mooncake", "tags": ["inference"]}
{"id": "hf-dataset:mlfoundations/dclm-pool-7b-2x", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/dclm-pool-7b-2x", "date": "2024-09-16", "createdAt": "2024-06-20", "sourceUpdatedAt": "2024-09-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 221747 downloads.", "popularity": {"value": 221747, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/dclm-pool-7b-2x", "tags": ["datasets", "region:us"]}
{"id": "github:rnchg/apt", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "rnchg/APT", "date": "2025-12-13", "createdAt": "2024-06-19", "sourceUpdatedAt": "2025-12-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Productivity Tool - Free and open source, improve user productivity, and protect privacy and data security. Including but not limited to: built-in local exclusive ChatGPT, DeepSeek, Phi, Qwen and other models, one-click batch intelligent processing of pi...", "popularity": {"value": 772, "label": "stars"}, "url": "https://github.com/rnchg/APT", "tags": ["inference", "video-tools"]}
{"id": "hf-dataset:mlfoundations/dclm-baseline-1.0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/dclm-baseline-1.0", "date": "2024-07-22", "createdAt": "2024-06-17", "sourceUpdatedAt": "2024-07-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 620356 downloads.", "popularity": {"value": 620356, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0", "tags": ["arxiv:2406.11794", "datasets", "license:cc-by-4.0", "region:us"]}
{"id": "hf-dataset:SaylorTwift/bbh", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "SaylorTwift/bbh", "date": "2024-06-16", "createdAt": "2024-06-12", "sourceUpdatedAt": "2024-06-16", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 50490 downloads.", "popularity": {"value": 50490, "label": "downloads"}, "url": "https://huggingface.co/datasets/SaylorTwift/bbh", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-model:lpiccinelli/unidepth-v2-vitl14", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "lpiccinelli/unidepth-v2-vitl14", "date": "2024-06-12", "createdAt": "2024-06-12", "sourceUpdatedAt": "2024-06-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 12418529 downloads and tags: UniDepth, pytorch, safetensors, model_hub_mixin.", "popularity": {"value": 12418529, "label": "downloads"}, "url": "https://huggingface.co/lpiccinelli/unidepth-v2-vitl14", "tags": ["llm", "model_hub_mixin", "monocular-metric-depth-estimation", "pytorch", "pytorch_model_hub_mixin", "region:us", "safetensors", "unidepth"]}
{"id": "github:bosun-ai/swiftide", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "bosun-ai/swiftide", "date": "2026-05-29", "createdAt": "2024-06-09", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fast, streaming indexing, query, and agentic LLM applications in Rust", "popularity": {"value": 703, "label": "stars"}, "url": "https://github.com/bosun-ai/swiftide", "tags": ["agents", "llmops"]}
{"id": "github:neonwatty/meme-search", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "neonwatty/meme-search", "date": "2026-05-31", "createdAt": "2024-06-08", "sourceUpdatedAt": "2026-05-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The open source Meme Search Engine and Finder.  Free and built to self-host locally with Python, Ruby, and Docker.", "popularity": {"value": 676, "label": "stars"}, "url": "https://github.com/neonwatty/meme-search", "tags": ["tools", "vector-database"]}
{"id": "github:zoicware/removewindowsai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zoicware/RemoveWindowsAI", "date": "2026-06-03", "createdAt": "2024-06-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Force Remove Copilot, Recall and More in Windows 11", "popularity": {"value": 11945, "label": "stars"}, "url": "https://github.com/zoicware/RemoveWindowsAI", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:lmms-lab/Video-MME", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lmms-lab/Video-MME", "date": "2024-07-04", "createdAt": "2024-06-07", "sourceUpdatedAt": "2024-07-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 98174 downloads.", "popularity": {"value": 98174, "label": "downloads"}, "url": "https://huggingface.co/datasets/lmms-lab/Video-MME", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "modality:video"]}
{"id": "hf-dataset:llamafactory/tiny-supervised-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "llamafactory/tiny-supervised-dataset", "date": "2024-06-10", "createdAt": "2024-06-07", "sourceUpdatedAt": "2024-06-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 74988 downloads.", "popularity": {"value": 74988, "label": "downloads"}, "url": "https://huggingface.co/datasets/llamafactory/tiny-supervised-dataset", "tags": ["datasets", "format:json", "language:en", "language:zh", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "github:samuraigpt/text-to-video-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SamurAIGPT/Text-To-Video-AI", "date": "2026-02-05", "createdAt": "2024-06-06", "sourceUpdatedAt": "2026-02-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Generate video from text using AI", "popularity": {"value": 741, "label": "stars"}, "url": "https://github.com/SamurAIGPT/Text-To-Video-AI", "tags": ["text-to-image", "video-tools"]}
{"id": "github:0xplaygrounds/rig", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "0xPlaygrounds/rig", "date": "2026-06-02", "createdAt": "2024-06-05", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "⚙️🦀 Build modular and scalable LLM Applications in Rust", "popularity": {"value": 7517, "label": "stars"}, "url": "https://github.com/0xPlaygrounds/rig", "tags": ["llmops", "tools"]}
{"id": "github:lazyagi/lazyllm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "LazyAGI/LazyLLM", "date": "2026-06-03", "createdAt": "2024-06-04", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Easiest and laziest way for  building multi-agent LLMs applications.", "popularity": {"value": 3838, "label": "stars"}, "url": "https://github.com/LazyAGI/LazyLLM", "tags": ["agents", "ai-agent"]}
{"id": "github:gojasper/flash-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "gojasper/flash-diffusion", "date": "2025-03-11", "createdAt": "2024-06-04", "sourceUpdatedAt": "2025-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Flash Diffusion — accelerating conditional diffusion models (AAAI 2025 Oral)", "popularity": {"value": 663, "label": "stars"}, "url": "https://github.com/gojasper/flash-diffusion", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:PromptEval/PromptEval_MMLU_correctness", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "PromptEval/PromptEval_MMLU_correctness", "date": "2024-06-07", "createdAt": "2024-06-04", "sourceUpdatedAt": "2024-06-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 85435 downloads.", "popularity": {"value": 85435, "label": "downloads"}, "url": "https://huggingface.co/datasets/PromptEval/PromptEval_MMLU_correctness", "tags": ["arxiv:2405.17202", "datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-model:Qwen/Qwen2-1.5B-Instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Qwen/Qwen2-1.5B-Instruct", "date": "2024-06-03", "createdAt": "2024-06-03", "sourceUpdatedAt": "2024-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4335610 downloads and tags: transformers, safetensors, qwen2, text-generation.", "popularity": {"value": 4335610, "label": "downloads"}, "url": "https://huggingface.co/Qwen/Qwen2-1.5B-Instruct", "tags": ["chat", "conversational", "en", "license:apache-2.0", "llm", "qwen2", "safetensors", "text-generation"]}
{"id": "github:lmcache/lmcache", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "LMCache/LMCache", "date": "2026-06-04", "createdAt": "2024-05-28", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LMCache: Supercharge Your LLM with the Fastest KV Cache Layer", "popularity": {"value": 8410, "label": "stars"}, "url": "https://github.com/LMCache/LMCache", "tags": ["inference"]}
{"id": "github:datawhalechina/happy-llm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "datawhalechina/happy-llm", "date": "2026-05-06", "createdAt": "2024-05-28", "sourceUpdatedAt": "2026-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📚 从零开始构建大模型", "popularity": {"value": 30855, "label": "stars"}, "url": "https://github.com/datawhalechina/happy-llm", "tags": ["llm", "tools"]}
{"id": "hf-dataset:HuggingFaceFW/fineweb-edu", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/fineweb-edu", "date": "2025-07-11", "createdAt": "2024-05-28", "sourceUpdatedAt": "2025-07-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 519083 downloads.", "popularity": {"value": 519083, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu", "tags": ["arxiv:2109.07445", "arxiv:2401.10020", "arxiv:2404.14219", "arxiv:2406.17557", "datasets", "doi:10.57967/hf/2497", "format:parquet", "language:en"]}
{"id": "hf-dataset:HuggingFaceFW/fineweb-edu-score-2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/fineweb-edu-score-2", "date": "2025-07-11", "createdAt": "2024-05-28", "sourceUpdatedAt": "2025-07-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 154711 downloads.", "popularity": {"value": 154711, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu-score-2", "tags": ["arxiv:2109.07445", "arxiv:2401.10020", "arxiv:2404.14219", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets"]}
{"id": "github:2noise/chattts", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "2noise/ChatTTS", "date": "2026-04-10", "createdAt": "2024-05-27", "sourceUpdatedAt": "2026-04-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A generative speech model for daily dialogue.", "popularity": {"value": 39382, "label": "stars"}, "url": "https://github.com/2noise/ChatTTS", "tags": ["llm", "tools"]}
{"id": "github:upsonic/upsonic", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Upsonic/Upsonic", "date": "2026-05-20", "createdAt": "2024-05-26", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build autonomous AI agents in Python.", "popularity": {"value": 7870, "label": "stars"}, "url": "https://github.com/Upsonic/Upsonic", "tags": ["agents", "rag"]}
{"id": "hf-dataset:AquaV/genshin-voices-separated", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AquaV/genshin-voices-separated", "date": "2024-07-06", "createdAt": "2024-05-26", "sourceUpdatedAt": "2024-07-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 112274 downloads.", "popularity": {"value": 112274, "label": "downloads"}, "url": "https://huggingface.co/datasets/AquaV/genshin-voices-separated", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:m-a-p/PIN-200M", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "m-a-p/PIN-200M", "date": "2026-04-15", "createdAt": "2024-05-25", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 155058 downloads.", "popularity": {"value": 155058, "label": "downloads"}, "url": "https://huggingface.co/datasets/m-a-p/PIN-200M", "tags": ["arxiv:2406.13923", "datasets", "format:json", "interleaved", "language:en", "language:zh", "library:datasets", "library:mlcroissant"]}
{"id": "github:cherryhq/cherry-studio", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "CherryHQ/cherry-studio", "date": "2026-06-04", "createdAt": "2024-05-24", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs", "popularity": {"value": 46828, "label": "stars"}, "url": "https://github.com/CherryHQ/cherry-studio", "tags": ["agents", "ai-agent"]}
{"id": "github:dontizi/remind", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "DonTizi/ReMind", "date": "2024-12-26", "createdAt": "2024-05-22", "sourceUpdatedAt": "2024-12-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Your Local Artificial Memory on your Device.", "popularity": {"value": 511, "label": "stars"}, "url": "https://github.com/DonTizi/ReMind", "tags": ["tools", "vector-database"]}
{"id": "hf-model:dphn/dolphin-2.9.1-yi-1.5-34b", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "dphn/dolphin-2.9.1-yi-1.5-34b", "date": "2024-05-18", "createdAt": "2024-05-18", "sourceUpdatedAt": "2024-05-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4734319 downloads and tags: transformers, safetensors, llama, text-generation.", "popularity": {"value": 4734319, "label": "downloads"}, "url": "https://huggingface.co/dphn/dolphin-2.9.1-yi-1.5-34b", "tags": ["axolotl", "conversational", "dataset:cognitivecomputations/dolphin-2.9", "generated_from_trainer", "llama", "llm", "safetensors", "text-generation"]}
{"id": "hf-dataset:llamafactory/demo_data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "llamafactory/demo_data", "date": "2024-07-18", "createdAt": "2024-05-17", "sourceUpdatedAt": "2024-07-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 93591 downloads.", "popularity": {"value": 93591, "label": "downloads"}, "url": "https://huggingface.co/datasets/llamafactory/demo_data", "tags": ["datasets", "language:en", "language:zh", "license:apache-2.0", "llama-factory", "modality:text", "region:us", "size_categories:1k<n<10k"]}
{"id": "github:timescale/pgai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "timescale/pgai", "date": "2026-05-27", "createdAt": "2024-05-16", "sourceUpdatedAt": "2026-05-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL", "popularity": {"value": 5800, "label": "stars"}, "url": "https://github.com/timescale/pgai", "tags": ["rag"]}
{"id": "github:poloclub/transformer-explainer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "poloclub/transformer-explainer", "date": "2026-05-21", "createdAt": "2024-05-16", "sourceUpdatedAt": "2026-05-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization", "popularity": {"value": 7734, "label": "stars"}, "url": "https://github.com/poloclub/transformer-explainer", "tags": ["generative-ai", "tools"]}
{"id": "github:sigoden/llm-functions", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "sigoden/llm-functions", "date": "2025-06-25", "createdAt": "2024-05-16", "sourceUpdatedAt": "2025-06-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Easily create LLM tools and agents using plain Bash/JavaScript/Python functions.", "popularity": {"value": 753, "label": "stars"}, "url": "https://github.com/sigoden/llm-functions", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:LanguageBind/Open-Sora-Plan-v1.1.0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "LanguageBind/Open-Sora-Plan-v1.1.0", "date": "2024-07-01", "createdAt": "2024-05-16", "sourceUpdatedAt": "2024-07-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 115060 downloads.", "popularity": {"value": 115060, "label": "downloads"}, "url": "https://huggingface.co/datasets/LanguageBind/Open-Sora-Plan-v1.1.0", "tags": ["datasets", "format:webdataset", "library:datasets", "library:mlcroissant", "library:webdataset", "license:mit", "modality:text", "region:us"]}
{"id": "github:gpustack/gpustack", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "gpustack/gpustack", "date": "2026-06-03", "createdAt": "2024-05-11", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A GPU cluster manager that configures and orchestrates inference engines like vLLM and SGLang for high-performance AI model deployment.", "popularity": {"value": 5097, "label": "stars"}, "url": "https://github.com/gpustack/gpustack", "tags": ["inference"]}
{"id": "hf-dataset:TIGER-Lab/MMLU-Pro", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "TIGER-Lab/MMLU-Pro", "date": "2026-05-02", "createdAt": "2024-05-08", "sourceUpdatedAt": "2026-05-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 154285 downloads.", "popularity": {"value": 154285, "label": "downloads"}, "url": "https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro", "tags": ["arxiv:2406.01574", "benchmark:eval-yaml", "benchmark:official", "datasets", "doi:10.57967/hf/2439", "evaluation", "format:parquet", "language:en"]}
{"id": "hf-dataset:banned-historical-archives/zhongyangribao", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "banned-historical-archives/zhongyangribao", "date": "2024-06-13", "createdAt": "2024-05-08", "sourceUpdatedAt": "2024-06-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 183925 downloads.", "popularity": {"value": 183925, "label": "downloads"}, "url": "https://huggingface.co/datasets/banned-historical-archives/zhongyangribao", "tags": ["datasets", "region:us"]}
{"id": "github:oumi-ai/oumi", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "oumi-ai/oumi", "date": "2026-06-03", "createdAt": "2024-05-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Easily fine-tune, evaluate and deploy Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, or any open source LLM / VLM!", "popularity": {"value": 9281, "label": "stars"}, "url": "https://github.com/oumi-ai/oumi", "tags": ["inference"]}
{"id": "hf-dataset:Zyphra/Zyda", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Zyphra/Zyda", "date": "2024-06-19", "createdAt": "2024-05-04", "sourceUpdatedAt": "2024-06-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63105 downloads.", "popularity": {"value": 63105, "label": "downloads"}, "url": "https://huggingface.co/datasets/Zyphra/Zyda", "tags": ["arxiv:2101.00027", "arxiv:2405.16712", "arxiv:2406.01981", "datasets", "doi:10.57967/hf/2394", "language:en", "license:odc-by", "modality:text"]}
{"id": "github:openbestof/awesome-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "openbestof/awesome-ai", "date": "2024-05-04", "createdAt": "2024-05-04", "sourceUpdatedAt": "2024-05-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of awesome AI tools, frameworks, api, software and resources.", "popularity": {"value": 557, "label": "stars"}, "url": "https://github.com/openbestof/awesome-ai", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-model:MahmoudAshraf/mms-300m-1130-forced-aligner", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "MahmoudAshraf/mms-300m-1130-forced-aligner", "date": "2024-05-02", "createdAt": "2024-05-02", "sourceUpdatedAt": "2024-05-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2792873 downloads and tags: transformers, pytorch, safetensors, wav2vec2.", "popularity": {"value": 2792873, "label": "downloads"}, "url": "https://huggingface.co/MahmoudAshraf/mms-300m-1130-forced-aligner", "tags": ["audio", "automatic-speech-recognition", "mms", "pytorch", "safetensors", "transformers", "voice", "wav2vec2"]}
{"id": "github:genkit-ai/genkit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "genkit-ai/genkit", "date": "2026-06-04", "createdAt": "2024-04-29", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source framework for building AI-powered apps in JavaScript, Go, and Python, built and used in production by Google", "popularity": {"value": 6090, "label": "stars"}, "url": "https://github.com/genkit-ai/genkit", "tags": ["rag"]}
{"id": "github:shubhamsaboo/awesome-llm-apps", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Shubhamsaboo/awesome-llm-apps", "date": "2026-06-03", "createdAt": "2024-04-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "100+ AI Agent & RAG apps you can actually run — clone, customize, ship.", "popularity": {"value": 112806, "label": "stars"}, "url": "https://github.com/Shubhamsaboo/awesome-llm-apps", "tags": ["agents", "rag"]}
{"id": "github:intentee/paddler", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "intentee/paddler", "date": "2026-06-03", "createdAt": "2024-04-27", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source LLM/VLM load balancer and serving platform for self-hosting LLMs (and VLMs) at scale 🏓🦙 Alternative to projects like llm-d, Docker Model Runner, etc but with less moving parts and simple deployments built around ggml ecosystem. Runs on CPU and GPU.", "popularity": {"value": 1588, "label": "stars"}, "url": "https://github.com/intentee/paddler", "tags": ["inference", "llmops"]}
{"id": "hf-dataset:labelmaker/arkit_labelmaker", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "labelmaker/arkit_labelmaker", "date": "2025-03-25", "createdAt": "2024-04-24", "sourceUpdatedAt": "2025-03-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 174249 downloads.", "popularity": {"value": 174249, "label": "downloads"}, "url": "https://huggingface.co/datasets/labelmaker/arkit_labelmaker", "tags": ["3d semantic segmentation", "arxiv:2410.13924", "datasets", "doi:10.57967/hf/2389", "indoor 3d scene dataset", "language:en", "license:bsd", "pointcloud-segmentation"]}
{"id": "github:pydantic/logfire", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pydantic/logfire", "date": "2026-06-03", "createdAt": "2024-04-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI observability platform for production LLM and agent systems.", "popularity": {"value": 4280, "label": "stars"}, "url": "https://github.com/pydantic/logfire", "tags": ["agents", "ai-tools"]}
{"id": "hf-model:FinLang/finance-embeddings-investopedia", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "FinLang/finance-embeddings-investopedia", "date": "2024-04-22", "createdAt": "2024-04-22", "sourceUpdatedAt": "2024-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2808853 downloads and tags: sentence-transformers, safetensors, bert, feature-extraction.", "popularity": {"value": 2808853, "label": "downloads"}, "url": "https://huggingface.co/FinLang/finance-embeddings-investopedia", "tags": ["bert", "embeddings", "endpoints_compatible", "feature-extraction", "license:cc-by-nc-4.0", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "hf-model:Alibaba-NLP/gte-large-en-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Alibaba-NLP/gte-large-en-v1.5", "date": "2024-04-20", "createdAt": "2024-04-20", "sourceUpdatedAt": "2024-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1636771 downloads and tags: transformers, onnx, safetensors, new.", "popularity": {"value": 1636771, "label": "downloads"}, "url": "https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5", "tags": ["embeddings", "feature-extraction", "gte", "mteb", "new", "onnx", "safetensors", "sentence-transformers"]}
{"id": "github:wangrongsheng/awesome-llm-resources", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "WangRongsheng/awesome-LLM-resources", "date": "2026-06-04", "createdAt": "2024-04-19", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🧑‍🚀 全世界最好的LLM资料总结（多模态生成、Agent、辅助编程、AI审稿、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型） | Summary of the world's best LLM resources.", "popularity": {"value": 8473, "label": "stars"}, "url": "https://github.com/WangRongsheng/awesome-LLM-resources", "tags": ["agents", "rag"]}
{"id": "github:sylphai-inc/adalflow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SylphAI-Inc/AdalFlow", "date": "2026-05-29", "createdAt": "2024-04-19", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AdalFlow: The library to build & auto-optimize LLM applications.", "popularity": {"value": 4159, "label": "stars"}, "url": "https://github.com/SylphAI-Inc/AdalFlow", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:HuggingFaceFW/fineweb", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceFW/fineweb", "date": "2025-07-11", "createdAt": "2024-04-18", "sourceUpdatedAt": "2025-07-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1078108 downloads.", "popularity": {"value": 1078108, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceFW/fineweb", "tags": ["arxiv:2109.07445", "arxiv:2306.01116", "arxiv:2406.17557", "datasets", "doi:10.57967/hf/2493", "language:en", "license:odc-by", "modality:tabular"]}
{"id": "github:prometheus-eval/prometheus-eval", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "prometheus-eval/prometheus-eval", "date": "2025-04-25", "createdAt": "2024-04-18", "sourceUpdatedAt": "2025-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Evaluate your LLM's response with Prometheus and GPT4 💯", "popularity": {"value": 1090, "label": "stars"}, "url": "https://github.com/prometheus-eval/prometheus-eval", "tags": ["evaluation", "llmops"]}
{"id": "hf-dataset:livecodebench/code_generation_lite", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "livecodebench/code_generation_lite", "date": "2025-06-05", "createdAt": "2024-04-16", "sourceUpdatedAt": "2025-06-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71907 downloads.", "popularity": {"value": 71907, "label": "downloads"}, "url": "https://huggingface.co/datasets/livecodebench/code_generation_lite", "tags": ["arxiv:2403.07974", "code", "code generation", "datasets", "license:cc", "region:us", "size_categories:n<1k"]}
{"id": "github:firecrawl/firecrawl", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "firecrawl/firecrawl", "date": "2026-06-04", "createdAt": "2024-04-15", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The API to search, scrape, and interact with the web at scale. 🔥", "popularity": {"value": 128298, "label": "stars"}, "url": "https://github.com/firecrawl/firecrawl", "tags": ["llm", "tools"]}
{"id": "hf-dataset:HuggingFaceM4/the_cauldron", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceM4/the_cauldron", "date": "2024-05-06", "createdAt": "2024-04-11", "sourceUpdatedAt": "2024-05-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 710853 downloads.", "popularity": {"value": 710853, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceM4/the_cauldron", "tags": ["arxiv:1603.07396", "arxiv:1612.00837", "arxiv:1612.06890", "arxiv:1709.00103", "arxiv:1710.07300", "arxiv:1912.03098", "arxiv:2003.12462", "arxiv:2205.00363"]}
{"id": "hf-dataset:cot-leaderboard/cot-eval-traces-2.0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cot-leaderboard/cot-eval-traces-2.0", "date": "2025-02-26", "createdAt": "2024-04-10", "sourceUpdatedAt": "2025-02-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 122440 downloads.", "popularity": {"value": 122440, "label": "downloads"}, "url": "https://huggingface.co/datasets/cot-leaderboard/cot-eval-traces-2.0", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:openrail", "modality:text"]}
{"id": "github:packtpublishing/llm-engineers-handbook", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "PacktPublishing/LLM-Engineers-Handbook", "date": "2026-04-22", "createdAt": "2024-04-09", "sourceUpdatedAt": "2026-04-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices", "popularity": {"value": 5085, "label": "stars"}, "url": "https://github.com/PacktPublishing/LLM-Engineers-Handbook", "tags": ["llmops", "rag"]}
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{"id": "hf-dataset:xlangai/DS-1000", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "xlangai/DS-1000", "date": "2024-09-19", "createdAt": "2024-04-09", "sourceUpdatedAt": "2024-09-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 68621 downloads.", "popularity": {"value": 68621, "label": "downloads"}, "url": "https://huggingface.co/datasets/xlangai/DS-1000", "tags": ["code-generation", "datasets", "format:json", "language:code", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:bluuebunny/arxiv_metadata_by_year", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bluuebunny/arxiv_metadata_by_year", "date": "2024-09-07", "createdAt": "2024-04-07", "sourceUpdatedAt": "2024-09-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1712404 downloads.", "popularity": {"value": 1712404, "label": "downloads"}, "url": "https://huggingface.co/datasets/bluuebunny/arxiv_metadata_by_year", "tags": ["datasets", "doi:10.57967/hf/2056", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "github:miurla/morphic", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "miurla/morphic", "date": "2026-06-02", "createdAt": "2024-04-05", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An AI-powered search engine with a generative UI", "popularity": {"value": 8881, "label": "stars"}, "url": "https://github.com/miurla/morphic", "tags": ["generative-ai", "tools"]}
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{"id": "hf-dataset:ilsp/mmlu_greek", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ilsp/mmlu_greek", "date": "2024-05-20", "createdAt": "2024-04-01", "sourceUpdatedAt": "2024-05-20", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 53267 downloads.", "popularity": {"value": 53267, "label": "downloads"}, "url": "https://huggingface.co/datasets/ilsp/mmlu_greek", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:starlightsearch/embedanything", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "StarlightSearch/EmbedAnything", "date": "2026-05-07", "createdAt": "2024-03-31", "sourceUpdatedAt": "2026-05-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀", "popularity": {"value": 1255, "label": "stars"}, "url": "https://github.com/StarlightSearch/EmbedAnything", "tags": ["inference", "vector-database"]}
{"id": "github:scale3-labs/langtrace", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Scale3-Labs/langtrace", "date": "2025-11-17", "createdAt": "2024-03-30", "sourceUpdatedAt": "2025-11-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Langtrace 🔍 is an open-source,  Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊", "popularity": {"value": 1203, "label": "stars"}, "url": "https://github.com/Scale3-Labs/langtrace", "tags": ["evaluation", "llmops"]}
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{"id": "github:chrisliu298/awesome-llm-unlearning", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "chrisliu298/awesome-llm-unlearning", "date": "2026-05-12", "createdAt": "2024-03-27", "sourceUpdatedAt": "2026-05-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A resource repository for machine unlearning in large language models", "popularity": {"value": 595, "label": "stars"}, "url": "https://github.com/chrisliu298/awesome-llm-unlearning", "tags": ["evaluation"]}
{"id": "hf-dataset:ErikCikalleshi/new_york_times_news_2000_2007", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ErikCikalleshi/new_york_times_news_2000_2007", "date": "2024-03-27", "createdAt": "2024-03-27", "sourceUpdatedAt": "2024-03-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 280862 downloads.", "popularity": {"value": 280862, "label": "downloads"}, "url": "https://huggingface.co/datasets/ErikCikalleshi/new_york_times_news_2000_2007", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
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{"id": "github:streetlamb/tribe", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "StreetLamb/tribe", "date": "2025-10-27", "createdAt": "2024-03-24", "sourceUpdatedAt": "2025-10-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Low code tool to rapidly build and coordinate multi-agent teams", "popularity": {"value": 1078, "label": "stars"}, "url": "https://github.com/StreetLamb/tribe", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:lerobot/aloha_sim_transfer_cube_human", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lerobot/aloha_sim_transfer_cube_human", "date": "2026-03-05", "createdAt": "2024-03-23", "sourceUpdatedAt": "2026-03-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63720 downloads.", "popularity": {"value": 63720, "label": "downloads"}, "url": "https://huggingface.co/datasets/lerobot/aloha_sim_transfer_cube_human", "tags": ["aloha", "arxiv:2304.13705", "datasets", "format:parquet", "lerobot", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:lerobot/pusht", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lerobot/pusht", "date": "2025-09-27", "createdAt": "2024-03-23", "sourceUpdatedAt": "2025-09-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51226 downloads.", "popularity": {"value": 51226, "label": "downloads"}, "url": "https://huggingface.co/datasets/lerobot/pusht", "tags": ["arxiv:2303.04137", "datasets", "format:parquet", "lerobot", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "github:gurpreetkaurjethra/end-to-end-generative-ai-projects", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "GURPREETKAURJETHRA/END-TO-END-GENERATIVE-AI-PROJECTS", "date": "2025-01-24", "createdAt": "2024-03-21", "sourceUpdatedAt": "2025-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "End to End Generative AI Industry Projects on LLM Models with Deployment_Awesome LLM Projects", "popularity": {"value": 569, "label": "stars"}, "url": "https://github.com/GURPREETKAURJETHRA/END-TO-END-GENERATIVE-AI-PROJECTS", "tags": ["llmops", "tools"]}
{"id": "hf-dataset:raushan-testing-hf/videos-test", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "raushan-testing-hf/videos-test", "date": "2025-09-03", "createdAt": "2024-03-20", "sourceUpdatedAt": "2025-09-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 99027 downloads.", "popularity": {"value": 99027, "label": "downloads"}, "url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test", "tags": ["datasets", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:video", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:princeton-nlp/SWE-bench_Lite", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "princeton-nlp/SWE-bench_Lite", "date": "2025-03-03", "createdAt": "2024-03-19", "sourceUpdatedAt": "2025-03-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 118875 downloads.", "popularity": {"value": 118875, "label": "downloads"}, "url": "https://huggingface.co/datasets/princeton-nlp/SWE-bench_Lite", "tags": ["arxiv:2310.06770", "datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text"]}
{"id": "hf-dataset:Pokce/NewYorkTimes00-07", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Pokce/NewYorkTimes00-07", "date": "2024-03-18", "createdAt": "2024-03-18", "sourceUpdatedAt": "2024-03-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53212 downloads.", "popularity": {"value": 53212, "label": "downloads"}, "url": "https://huggingface.co/datasets/Pokce/NewYorkTimes00-07", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "github:wandb/openui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "wandb/openui", "date": "2026-05-20", "createdAt": "2024-03-17", "sourceUpdatedAt": "2026-05-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenUI let's you describe UI using your imagination, then see it rendered live.", "popularity": {"value": 22356, "label": "stars"}, "url": "https://github.com/wandb/openui", "tags": ["generative-ai", "tools"]}
{"id": "github:danny-avila/rag_api", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "danny-avila/rag_api", "date": "2026-04-24", "createdAt": "2024-03-17", "sourceUpdatedAt": "2026-04-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector", "popularity": {"value": 832, "label": "stars"}, "url": "https://github.com/danny-avila/rag_api", "tags": ["rag", "vector-database"]}
{"id": "github:ziqihuangg/awesome-evaluation-of-visual-generation", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ziqihuangg/Awesome-Evaluation-of-Visual-Generation", "date": "2026-05-08", "createdAt": "2024-03-16", "sourceUpdatedAt": "2026-05-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A list of works on evaluation of visual generation models, including evaluation metrics, models, and systems", "popularity": {"value": 448, "label": "stars"}, "url": "https://github.com/ziqihuangg/Awesome-Evaluation-of-Visual-Generation", "tags": ["evaluation"]}
{"id": "hf-dataset:BangumiBase/onepiece", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "BangumiBase/onepiece", "date": "2024-03-26", "createdAt": "2024-03-16", "sourceUpdatedAt": "2024-03-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54084 downloads.", "popularity": {"value": 54084, "label": "downloads"}, "url": "https://huggingface.co/datasets/BangumiBase/onepiece", "tags": ["art", "datasets", "license:mit", "modality:image", "region:us", "size_categories:10k<n<100k"]}
{"id": "hf-model:BAAI/bge-reranker-v2-m3", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-reranker-v2-m3", "date": "2024-03-15", "createdAt": "2024-03-15", "sourceUpdatedAt": "2024-03-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 14225864 downloads and tags: sentence-transformers, safetensors, xlm-roberta, text-classification.", "popularity": {"value": 14225864, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-reranker-v2-m3", "tags": ["arxiv:2312.15503", "embeddings", "multilingual", "safetensors", "sentence-transformers", "text-classification", "text-embeddings-inference", "transformers"]}
{"id": "github:openhands/openhands", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "OpenHands/OpenHands", "date": "2026-06-04", "createdAt": "2024-03-13", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🙌 OpenHands: AI-Driven Development", "popularity": {"value": 75771, "label": "stars"}, "url": "https://github.com/OpenHands/OpenHands", "tags": ["agent", "agents", "artificial-intelligence", "chatgpt", "claude-ai", "cli", "developer-tools"]}
{"id": "github:canner/wrenai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Canner/WrenAI", "date": "2026-06-04", "createdAt": "2024-03-13", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Give AI agents the context to query business data correctly through the open context layer that gives AI agents grounded, governed memory, context, SQL across 20+ data sources, that helps you build agentic GenBI, text-to-sql, dashboards, and agentic analytics.", "popularity": {"value": 15420, "label": "stars"}, "url": "https://github.com/Canner/WrenAI", "tags": ["agents", "rag"]}
{"id": "hf-dataset:bastao/VeraCruz_PT-BR", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bastao/VeraCruz_PT-BR", "date": "2025-07-21", "createdAt": "2024-03-13", "sourceUpdatedAt": "2025-07-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 90466 downloads.", "popularity": {"value": 90466, "label": "downloads"}, "url": "https://huggingface.co/datasets/bastao/VeraCruz_PT-BR", "tags": ["br", "brazil", "brazilian", "datasets", "format:parquet", "language:pt", "library:dask", "library:datasets"]}
{"id": "hf-dataset:occiglot/tokenizer-wiki-bench", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "occiglot/tokenizer-wiki-bench", "date": "2024-04-23", "createdAt": "2024-03-13", "sourceUpdatedAt": "2024-04-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 114606 downloads.", "popularity": {"value": 114606, "label": "downloads"}, "url": "https://huggingface.co/datasets/occiglot/tokenizer-wiki-bench", "tags": ["arxiv:2012.15613", "datasets", "format:parquet", "language:af", "language:ar", "language:bg", "language:ca", "language:cs"]}
{"id": "hf-dataset:baber/uspto_raw", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "baber/uspto_raw", "date": "2024-03-13", "createdAt": "2024-03-12", "sourceUpdatedAt": "2024-03-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 96528 downloads.", "popularity": {"value": 96528, "label": "downloads"}, "url": "https://huggingface.co/datasets/baber/uspto_raw", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "github:tencentarc/brushnet", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "TencentARC/BrushNet", "date": "2024-12-17", "createdAt": "2024-03-10", "sourceUpdatedAt": "2024-12-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[ECCV 2024] The official implementation of paper \"BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion\"", "popularity": {"value": 1737, "label": "stars"}, "url": "https://github.com/TencentARC/BrushNet", "tags": ["text-to-image", "tools"]}
{"id": "github:decodingai-magazine/llm-twin-course", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "decodingai-magazine/llm-twin-course", "date": "2026-04-20", "createdAt": "2024-03-08", "sourceUpdatedAt": "2026-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴", "popularity": {"value": 4350, "label": "stars"}, "url": "https://github.com/decodingai-magazine/llm-twin-course", "tags": ["llmops", "tools"]}
{"id": "github:evolvinglmms-lab/lmms-eval", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "EvolvingLMMs-Lab/lmms-eval", "date": "2026-06-02", "createdAt": "2024-03-07", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks", "popularity": {"value": 4191, "label": "stars"}, "url": "https://github.com/EvolvingLMMs-Lab/lmms-eval", "tags": ["evaluation", "video-tools"]}
{"id": "hf-model:mixedbread-ai/mxbai-embed-large-v1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "mixedbread-ai/mxbai-embed-large-v1", "date": "2024-03-07", "createdAt": "2024-03-07", "sourceUpdatedAt": "2024-03-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4768194 downloads and tags: sentence-transformers, onnx, safetensors, openvino.", "popularity": {"value": 4768194, "label": "downloads"}, "url": "https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1", "tags": ["bert", "embeddings", "feature-extraction", "gguf", "mteb", "onnx", "openvino", "safetensors"]}
{"id": "github:modeltc/lightcompress", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ModelTC/LightCompress", "date": "2026-05-14", "createdAt": "2024-03-06", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[EMNLP 2024 & AAAI 2026] A powerful toolkit for compressing large models including LLMs, VLMs, and video generative models.", "popularity": {"value": 721, "label": "stars"}, "url": "https://github.com/ModelTC/LightCompress", "tags": ["evaluation", "video-tools"]}
{"id": "github:fofr/cog-face-to-many", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "fofr/cog-face-to-many", "date": "2024-04-09", "createdAt": "2024-03-05", "sourceUpdatedAt": "2024-04-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Turn any face into a video game character, pixel art, claymation, 3D or toy", "popularity": {"value": 1366, "label": "stars"}, "url": "https://github.com/fofr/cog-face-to-many", "tags": ["text-to-image", "video-tools"]}
{"id": "hf-dataset:DL3DV/DL3DV-ALL-480P", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "DL3DV/DL3DV-ALL-480P", "date": "2024-09-02", "createdAt": "2024-03-04", "sourceUpdatedAt": "2024-09-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48463 downloads.", "popularity": {"value": 48463, "label": "downloads"}, "url": "https://huggingface.co/datasets/DL3DV/DL3DV-ALL-480P", "tags": ["3d gaussian", "3d vision", "dataset", "datasets", "image to 3d", "nerf", "novel view synthesis", "region:us"]}
{"id": "github:baai-agents/cradle", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "BAAI-Agents/Cradle", "date": "2024-11-07", "createdAt": "2024-03-03", "sourceUpdatedAt": "2024-11-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The Cradle framework is a first attempt at General Computer Control (GCC). Cradle supports agents to ace any computer task by enabling strong reasoning abilities, self-improvment, and skill curation, in a standardized general environment with minimal requir...", "popularity": {"value": 2532, "label": "stars"}, "url": "https://github.com/BAAI-Agents/Cradle", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:OpenDriveLab/OpenScene", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "OpenDriveLab/OpenScene", "date": "2025-04-28", "createdAt": "2024-03-02", "sourceUpdatedAt": "2025-04-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 74024 downloads.", "popularity": {"value": 74024, "label": "downloads"}, "url": "https://huggingface.co/datasets/OpenDriveLab/OpenScene", "tags": ["datasets", "license:cc-by-nc-sa-4.0", "region:us"]}
{"id": "github:skyvern-ai/skyvern", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Skyvern-AI/skyvern", "date": "2026-06-04", "createdAt": "2024-02-28", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Automate browser based workflows with AI", "popularity": {"value": 21812, "label": "stars"}, "url": "https://github.com/Skyvern-AI/skyvern", "tags": ["developer-tools", "llm"]}
{"id": "github:fofr/cog-face-to-sticker", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "fofr/cog-face-to-sticker", "date": "2024-03-01", "createdAt": "2024-02-28", "sourceUpdatedAt": "2024-03-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "face-to-sticker", "popularity": {"value": 645, "label": "stars"}, "url": "https://github.com/fofr/cog-face-to-sticker", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:argmaxinc/whisperkit-coreml", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "argmaxinc/whisperkit-coreml", "date": "2024-02-28", "createdAt": "2024-02-28", "sourceUpdatedAt": "2024-02-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 9539019 downloads and tags: whisperkit, coreml, whisper, asr.", "popularity": {"value": 9539019, "label": "downloads"}, "url": "https://huggingface.co/argmaxinc/whisperkit-coreml", "tags": ["asr", "audio", "automatic-speech-recognition", "coreml", "quantized", "region:us", "whisper", "whisperkit"]}
{"id": "github:seekstorm/seekstorm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SeekStorm/SeekStorm", "date": "2026-05-13", "createdAt": "2024-02-27", "sourceUpdatedAt": "2026-05-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.", "popularity": {"value": 1884, "label": "stars"}, "url": "https://github.com/SeekStorm/SeekStorm", "tags": ["tools", "vector-database"]}
{"id": "hf-dataset:gorilla-llm/Berkeley-Function-Calling-Leaderboard", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gorilla-llm/Berkeley-Function-Calling-Leaderboard", "date": "2026-04-29", "createdAt": "2024-02-27", "sourceUpdatedAt": "2026-04-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81867 downloads.", "popularity": {"value": 81867, "label": "downloads"}, "url": "https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard", "tags": ["datasets", "language:en", "license:apache-2.0", "region:us"]}
{"id": "github:shilin-lu/mace", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Shilin-LU/MACE", "date": "2026-04-03", "createdAt": "2024-02-27", "sourceUpdatedAt": "2026-04-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[CVPR 2024] \"MACE: Mass Concept Erasure in Diffusion Models\" (Official Implementation)", "popularity": {"value": 396, "label": "stars"}, "url": "https://github.com/Shilin-LU/MACE", "tags": ["text-to-image", "tools"]}
{"id": "github:parthsarthi03/raptor", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "parthsarthi03/raptor", "date": "2024-09-03", "createdAt": "2024-02-27", "sourceUpdatedAt": "2024-09-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval", "popularity": {"value": 1685, "label": "stars"}, "url": "https://github.com/parthsarthi03/raptor", "tags": ["rag", "vector-database"]}
{"id": "github:lavague-ai/lavague", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lavague-ai/LaVague", "date": "2025-01-21", "createdAt": "2024-02-26", "sourceUpdatedAt": "2025-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Large Action Model framework to develop AI Web Agents", "popularity": {"value": 6361, "label": "stars"}, "url": "https://github.com/lavague-ai/LaVague", "tags": ["agents", "rag"]}
{"id": "hf-dataset:DL3DV/DL3DV-ALL-960P", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "DL3DV/DL3DV-ALL-960P", "date": "2024-09-02", "createdAt": "2024-02-25", "sourceUpdatedAt": "2024-09-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71476 downloads.", "popularity": {"value": 71476, "label": "downloads"}, "url": "https://huggingface.co/datasets/DL3DV/DL3DV-ALL-960P", "tags": ["3d gaussian", "3d vision", "dataset", "datasets", "image to 3d", "nerf", "novel view synthesis", "region:us"]}
{"id": "github:composiohq/composio", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ComposioHQ/composio", "date": "2026-06-03", "createdAt": "2024-02-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Composio powers 1000+ toolkits, tool search, context management, authentication, and a sandboxed workbench to help you build AI agents that turn intent into action.", "popularity": {"value": 28604, "label": "stars"}, "url": "https://github.com/ComposioHQ/composio", "tags": ["agents", "llm"]}
{"id": "hf-dataset:Salesforce/lotsa_data", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Salesforce/lotsa_data", "date": "2025-01-21", "createdAt": "2024-02-22", "sourceUpdatedAt": "2025-01-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54334 downloads.", "popularity": {"value": 54334, "label": "downloads"}, "url": "https://huggingface.co/datasets/Salesforce/lotsa_data", "tags": ["arxiv:2402.02592", "datasets", "format:arrow", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:text", "modality:timeseries"]}
{"id": "github:zipstack/unstract", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Zipstack/unstract", "date": "2026-06-04", "createdAt": "2024-02-21", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows", "popularity": {"value": 6628, "label": "stars"}, "url": "https://github.com/Zipstack/unstract", "tags": ["developer-tools", "generative-ai"]}
{"id": "hf-model:playgroundai/playground-v2.5-1024px-aesthetic", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "playgroundai/playground-v2.5-1024px-aesthetic", "date": "2024-02-16", "createdAt": "2024-02-16", "sourceUpdatedAt": "2024-02-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 271740 downloads and tags: diffusers, safetensors, text-to-image, playground.", "popularity": {"value": 271740, "label": "downloads"}, "url": "https://huggingface.co/playgroundai/playground-v2.5-1024px-aesthetic", "tags": ["arxiv:2206.00364", "arxiv:2402.17245", "diffusers", "image-generation", "license:other", "playground", "region:us", "safetensors"]}
{"id": "github:ironjr/semantic-draw", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ironjr/semantic-draw", "date": "2025-06-01", "createdAt": "2024-02-15", "sourceUpdatedAt": "2025-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official code for the CVPR 2025 paper \"SemanticDraw: Towards Real-Time Interactive Content Creation from Image Diffusion Models.\"", "popularity": {"value": 589, "label": "stars"}, "url": "https://github.com/ironjr/semantic-draw", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:Kazimir-ai/text-to-image-prompts", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Kazimir-ai/text-to-image-prompts", "date": "2024-02-15", "createdAt": "2024-02-15", "sourceUpdatedAt": "2024-02-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 203772 downloads.", "popularity": {"value": 203772, "label": "downloads"}, "url": "https://huggingface.co/datasets/Kazimir-ai/text-to-image-prompts", "tags": ["datasets", "format:csv", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:apache-2.0"]}
{"id": "github:sciphi-ai/r2r", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "SciPhi-AI/R2R", "date": "2025-11-07", "createdAt": "2024-02-12", "sourceUpdatedAt": "2025-11-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.", "popularity": {"value": 7876, "label": "stars"}, "url": "https://github.com/SciPhi-AI/R2R", "tags": ["agents", "rag"]}
{"id": "github:alonzoleeeooo/awesome-text-to-image-studies", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AlonzoLeeeooo/awesome-text-to-image-studies", "date": "2026-04-25", "createdAt": "2024-02-11", "sourceUpdatedAt": "2026-04-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A collection of awesome text-to-image generation studies.", "popularity": {"value": 759, "label": "stars"}, "url": "https://github.com/AlonzoLeeeooo/awesome-text-to-image-studies", "tags": ["text-to-image", "tools"]}
{"id": "github:hanaokayuzu/gemini-api", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HanaokaYuzu/Gemini-API", "date": "2026-04-13", "createdAt": "2024-02-11", "sourceUpdatedAt": "2026-04-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "✨ Reverse-engineered Python API for Google Gemini web app", "popularity": {"value": 3117, "label": "stars"}, "url": "https://github.com/HanaokaYuzu/Gemini-API", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:espnet/yodas", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "espnet/yodas", "date": "2024-06-10", "createdAt": "2024-02-10", "sourceUpdatedAt": "2024-06-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 92364 downloads.", "popularity": {"value": 92364, "label": "downloads"}, "url": "https://huggingface.co/datasets/espnet/yodas", "tags": ["arxiv:2406.00899", "datasets", "license:cc-by-3.0", "region:us"]}
{"id": "hf-model:nomic-ai/nomic-embed-text-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "nomic-ai/nomic-embed-text-v1.5", "date": "2024-02-10", "createdAt": "2024-02-10", "sourceUpdatedAt": "2024-02-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 17972694 downloads and tags: sentence-transformers, onnx, safetensors, nomic_bert.", "popularity": {"value": 17972694, "label": "downloads"}, "url": "https://huggingface.co/nomic-ai/nomic-embed-text-v1.5", "tags": ["embeddings", "feature-extraction", "mteb", "nomic_bert", "onnx", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "hf-dataset:ibrahimhamamci/CT-RATE", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ibrahimhamamci/CT-RATE", "date": "2026-03-16", "createdAt": "2024-02-09", "sourceUpdatedAt": "2026-03-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 126612 downloads.", "popularity": {"value": 126612, "label": "downloads"}, "url": "https://huggingface.co/datasets/ibrahimhamamci/CT-RATE", "tags": ["3d-medical-imaging", "arxiv:2403.17834", "chest-ct", "computer-vision", "ct-rate", "datasets", "diagnostic-imaging", "foundation-model"]}
{"id": "hf-model:intfloat/multilingual-e5-large-instruct", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "intfloat/multilingual-e5-large-instruct", "date": "2024-02-08", "createdAt": "2024-02-08", "sourceUpdatedAt": "2024-02-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1617532 downloads and tags: sentence-transformers, onnx, safetensors, xlm-roberta.", "popularity": {"value": 1617532, "label": "downloads"}, "url": "https://huggingface.co/intfloat/multilingual-e5-large-instruct", "tags": ["embeddings", "feature-extraction", "mteb", "multilingual", "onnx", "safetensors", "sentence-transformers", "transformers"]}
{"id": "github:aishwaryanr/awesome-generative-ai-guide", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "aishwaryanr/awesome-generative-ai-guide", "date": "2026-05-19", "createdAt": "2024-02-06", "sourceUpdatedAt": "2026-05-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A one stop repository for generative AI research updates, interview resources, notebooks and much more!", "popularity": {"value": 26990, "label": "stars"}, "url": "https://github.com/aishwaryanr/awesome-generative-ai-guide", "tags": ["generative-ai", "tools"]}
{"id": "github:pingcap/autoflow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pingcap/autoflow", "date": "2026-04-27", "createdAt": "2024-02-05", "sourceUpdatedAt": "2026-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai", "popularity": {"value": 2788, "label": "stars"}, "url": "https://github.com/pingcap/autoflow", "tags": ["rag", "vector-database"]}
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{"id": "hf-dataset:CohereLabs/aya_collection", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "CohereLabs/aya_collection", "date": "2025-04-15", "createdAt": "2024-01-31", "sourceUpdatedAt": "2025-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 135385 downloads.", "popularity": {"value": 135385, "label": "downloads"}, "url": "https://huggingface.co/datasets/CohereLabs/aya_collection", "tags": ["arxiv:2402.06619", "datasets", "format:parquet", "language:ace", "language:afr", "language:amh", "language:ara", "language:aze"]}
{"id": "hf-model:nomic-ai/nomic-embed-text-v1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "nomic-ai/nomic-embed-text-v1", "date": "2024-01-31", "createdAt": "2024-01-31", "sourceUpdatedAt": "2024-01-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 6223589 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 6223589, "label": "downloads"}, "url": "https://huggingface.co/nomic-ai/nomic-embed-text-v1", "tags": ["embeddings", "feature-extraction", "mteb", "nomic_bert", "onnx", "pytorch", "safetensors", "sentence-similarity"]}
{"id": "github:mongodb-developer/genai-showcase", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mongodb-developer/GenAI-Showcase", "date": "2026-05-22", "createdAt": "2024-01-30", "sourceUpdatedAt": "2026-05-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "GenAI Cookbook", "popularity": {"value": 4230, "label": "stars"}, "url": "https://github.com/mongodb-developer/GenAI-Showcase", "tags": ["generative-ai", "tools"]}
{"id": "github:apache/burr", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "apache/burr", "date": "2026-06-03", "createdAt": "2024-01-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.", "popularity": {"value": 2019, "label": "stars"}, "url": "https://github.com/apache/burr", "tags": ["agents", "llmops"]}
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{"id": "github:scrapegraphai/scrapegraph-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ScrapeGraphAI/Scrapegraph-ai", "date": "2026-06-02", "createdAt": "2024-01-27", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Python scraper based on AI", "popularity": {"value": 26690, "label": "stars"}, "url": "https://github.com/ScrapeGraphAI/Scrapegraph-ai", "tags": ["llm", "tools"]}
{"id": "hf-model:BAAI/bge-m3", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-m3", "date": "2024-01-27", "createdAt": "2024-01-27", "sourceUpdatedAt": "2024-01-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 31719810 downloads and tags: sentence-transformers, pytorch, onnx, xlm-roberta.", "popularity": {"value": 31719810, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-m3", "tags": ["arxiv:2004.04906", "arxiv:2402.03216", "embeddings", "feature-extraction", "onnx", "pytorch", "sentence-similarity", "sentence-transformers"]}
{"id": "github:argmaxinc/argmax-oss-swift", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "argmaxinc/argmax-oss-swift", "date": "2026-06-02", "createdAt": "2024-01-26", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "On-device Speech AI for Apple Silicon", "popularity": {"value": 6171, "label": "stars"}, "url": "https://github.com/argmaxinc/argmax-oss-swift", "tags": ["inference"]}
{"id": "github:huggingface/lighteval", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "huggingface/lighteval", "date": "2026-05-29", "createdAt": "2024-01-26", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends", "popularity": {"value": 2433, "label": "stars"}, "url": "https://github.com/huggingface/lighteval", "tags": ["evaluation"]}
{"id": "github:openlit/openlit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "openlit/openlit", "date": "2026-06-03", "createdAt": "2024-01-23", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs.", "popularity": {"value": 2493, "label": "stars"}, "url": "https://github.com/openlit/openlit", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:McAuley-Lab/Amazon-Reviews-2023", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "McAuley-Lab/Amazon-Reviews-2023", "date": "2024-12-08", "createdAt": "2024-01-23", "sourceUpdatedAt": "2024-12-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54718 downloads.", "popularity": {"value": 54718, "label": "downloads"}, "url": "https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023", "tags": ["arxiv:2403.03952", "datasets", "language:en", "recommendation", "region:us", "reviews", "size_categories:10b<n<100b"]}
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{"id": "hf-dataset:DL3DV/DL3DV-Benchmark", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "DL3DV/DL3DV-Benchmark", "date": "2025-09-12", "createdAt": "2023-12-31", "sourceUpdatedAt": "2025-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71093 downloads.", "popularity": {"value": 71093, "label": "downloads"}, "url": "https://huggingface.co/datasets/DL3DV/DL3DV-Benchmark", "tags": ["3d gaussian splatting", "3d vision", "datasets", "generalizable nerf", "generative methods", "image-to-3d", "nerf", "novel view synthesis"]}
{"id": "github:alibaba/rtp-llm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "alibaba/rtp-llm", "date": "2026-06-04", "createdAt": "2023-12-27", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.", "popularity": {"value": 1178, "label": "stars"}, "url": "https://github.com/alibaba/rtp-llm", "tags": ["inference"]}
{"id": "github:arize-ai/openinference", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Arize-ai/openinference", "date": "2026-06-03", "createdAt": "2023-12-26", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "OpenTelemetry Instrumentation for AI Observability", "popularity": {"value": 1006, "label": "stars"}, "url": "https://github.com/Arize-ai/openinference", "tags": ["inference", "llmops"]}
{"id": "github:philippgille/chromem-go", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "philippgille/chromem-go", "date": "2026-05-17", "createdAt": "2023-12-24", "sourceUpdatedAt": "2026-05-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.", "popularity": {"value": 965, "label": "stars"}, "url": "https://github.com/philippgille/chromem-go", "tags": ["vector-database", "vector-db"]}
{"id": "github:howiehwong/trustllm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "HowieHwong/TrustLLM", "date": "2025-06-24", "createdAt": "2023-12-23", "sourceUpdatedAt": "2025-06-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[ICML 2024] TrustLLM: Trustworthiness in Large Language Models", "popularity": {"value": 626, "label": "stars"}, "url": "https://github.com/HowieHwong/TrustLLM", "tags": ["evaluation"]}
{"id": "hf-dataset:google/IFEval", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google/IFEval", "date": "2024-08-14", "createdAt": "2023-12-22", "sourceUpdatedAt": "2024-08-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 112260 downloads.", "popularity": {"value": 112260, "label": "downloads"}, "url": "https://huggingface.co/datasets/google/IFEval", "tags": ["arxiv:2311.07911", "datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "github:qualcomm/ai-hub-models", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "qualcomm/ai-hub-models", "date": "2026-06-04", "createdAt": "2023-12-20", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.", "popularity": {"value": 1067, "label": "stars"}, "url": "https://github.com/qualcomm/ai-hub-models", "tags": ["inference"]}
{"id": "github:tencentqqgylab/appagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "TencentQQGYLab/AppAgent", "date": "2025-03-19", "createdAt": "2023-12-20", "sourceUpdatedAt": "2025-03-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps.", "popularity": {"value": 6761, "label": "stars"}, "url": "https://github.com/TencentQQGYLab/AppAgent", "tags": ["agents", "generative-ai"]}
{"id": "hf-dataset:osv5m/osv5m", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "osv5m/osv5m", "date": "2024-04-27", "createdAt": "2023-12-20", "sourceUpdatedAt": "2024-04-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 586193 downloads.", "popularity": {"value": 586193, "label": "downloads"}, "url": "https://huggingface.co/datasets/osv5m/osv5m", "tags": ["datasets", "license:cc-by-sa-4.0", "region:us"]}
{"id": "hf-model:h94/IP-Adapter-FaceID", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "h94/IP-Adapter-FaceID", "date": "2023-12-20", "createdAt": "2023-12-20", "sourceUpdatedAt": "2023-12-20", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face model with 226822 downloads and tags: diffusers, text-to-image, stable-diffusion, en.", "popularity": {"value": 226822, "label": "downloads"}, "url": "https://huggingface.co/h94/IP-Adapter-FaceID", "tags": ["arxiv:2308.06721", "diffusers", "en", "image-generation", "region:us", "stable-diffusion", "text-to-image"]}
{"id": "hf-model:facebook/w2v-bert-2.0", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "facebook/w2v-bert-2.0", "date": "2023-12-19", "createdAt": "2023-12-19", "sourceUpdatedAt": "2023-12-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4273581 downloads and tags: transformers, safetensors, wav2vec2-bert, feature-extraction.", "popularity": {"value": 4273581, "label": "downloads"}, "url": "https://huggingface.co/facebook/w2v-bert-2.0", "tags": ["af", "am", "ar", "as", "embeddings", "feature-extraction", "safetensors", "transformers"]}
{"id": "hf-dataset:Gourieff/ReActor", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Gourieff/ReActor", "date": "2026-05-05", "createdAt": "2023-12-17", "sourceUpdatedAt": "2026-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 148439 downloads.", "popularity": {"value": 148439, "label": "downloads"}, "url": "https://huggingface.co/datasets/Gourieff/ReActor", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "hf-dataset:banned-historical-archives/banned-historical-archives", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "banned-historical-archives/banned-historical-archives", "date": "2025-10-19", "createdAt": "2023-12-17", "sourceUpdatedAt": "2025-10-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1449662 downloads.", "popularity": {"value": 1449662, "label": "downloads"}, "url": "https://huggingface.co/datasets/banned-historical-archives/banned-historical-archives", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:jat-project/jat-dataset-tokenized", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jat-project/jat-dataset-tokenized", "date": "2023-12-22", "createdAt": "2023-12-16", "sourceUpdatedAt": "2023-12-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 756833 downloads.", "popularity": {"value": 756833, "label": "downloads"}, "url": "https://huggingface.co/datasets/jat-project/jat-dataset-tokenized", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:timeseries", "region:us"]}
{"id": "github:infiniflow/ragflow", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "infiniflow/ragflow", "date": "2026-06-04", "createdAt": "2023-12-12", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs", "popularity": {"value": 81858, "label": "stars"}, "url": "https://github.com/infiniflow/ragflow", "tags": ["agents", "rag"]}
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{"id": "hf-dataset:sayan1101/gaia_filtered_text_only", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sayan1101/gaia_filtered_text_only", "date": "2023-12-08", "createdAt": "2023-12-08", "sourceUpdatedAt": "2023-12-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 57979 downloads.", "popularity": {"value": 57979, "label": "downloads"}, "url": "https://huggingface.co/datasets/sayan1101/gaia_filtered_text_only", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
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{"id": "github:prithivirajdamodaran/flashrank", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "PrithivirajDamodaran/FlashRank", "date": "2026-01-01", "createdAt": "2023-12-04", "sourceUpdatedAt": "2026-01-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Lite & Super-fast re-ranking for your search & retrieval pipelines.  Supports SoTA Listwise and Pairwise reranking based on LLMs and  cross-encoders and more.  Created by Prithivi Da, open for PRs & Collaborations.", "popularity": {"value": 981, "label": "stars"}, "url": "https://github.com/PrithivirajDamodaran/FlashRank", "tags": ["rag", "vector-database"]}
{"id": "hf-model:WhereIsAI/UAE-Large-V1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "WhereIsAI/UAE-Large-V1", "date": "2023-12-04", "createdAt": "2023-12-04", "sourceUpdatedAt": "2023-12-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1710492 downloads and tags: sentence-transformers, onnx, safetensors, openvino.", "popularity": {"value": 1710492, "label": "downloads"}, "url": "https://huggingface.co/WhereIsAI/UAE-Large-V1", "tags": ["bert", "embeddings", "feature-extraction", "mteb", "onnx", "openvino", "safetensors", "sentence-transformers"]}
{"id": "github:wooyeolbaek/attention-map-diffusers", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "wooyeolbaek/attention-map-diffusers", "date": "2026-02-02", "createdAt": "2023-12-02", "sourceUpdatedAt": "2026-02-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🚀 Cross attention map tools for huggingface/diffusers", "popularity": {"value": 406, "label": "stars"}, "url": "https://github.com/wooyeolbaek/attention-map-diffusers", "tags": ["developer-tools", "text-to-image"]}
{"id": "github:open-compass/vlmevalkit", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "open-compass/VLMEvalKit", "date": "2026-06-02", "createdAt": "2023-12-01", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks", "popularity": {"value": 4187, "label": "stars"}, "url": "https://github.com/open-compass/VLMEvalKit", "tags": ["evaluation"]}
{"id": "hf-dataset:deepinv/images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "deepinv/images", "date": "2026-02-16", "createdAt": "2023-12-01", "sourceUpdatedAt": "2026-02-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 82130 downloads.", "popularity": {"value": 82130, "label": "downloads"}, "url": "https://huggingface.co/datasets/deepinv/images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:bsd-3-clause", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:MMInstruction/ArxivCap", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "MMInstruction/ArxivCap", "date": "2024-10-03", "createdAt": "2023-12-01", "sourceUpdatedAt": "2024-10-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 155790 downloads.", "popularity": {"value": 155790, "label": "downloads"}, "url": "https://huggingface.co/datasets/MMInstruction/ArxivCap", "tags": ["arxiv", "arxiv:2403.00231", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:Yash2998db/GAIA", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Yash2998db/GAIA", "date": "2023-11-30", "createdAt": "2023-11-30", "sourceUpdatedAt": "2023-11-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48326 downloads.", "popularity": {"value": 48326, "label": "downloads"}, "url": "https://huggingface.co/datasets/Yash2998db/GAIA", "tags": ["datasets", "region:us"]}
{"id": "github:unslothai/unsloth", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "unslothai/unsloth", "date": "2026-06-03", "createdAt": "2023-11-29", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Unsloth Studio is a web UI for training and running open models like Gemma 4, Qwen3.6, DeepSeek, gpt-oss locally.", "popularity": {"value": 65681, "label": "stars"}, "url": "https://github.com/unslothai/unsloth", "tags": ["llm", "ui-demo"]}
{"id": "github:azure-samples/contoso-chat", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Azure-Samples/contoso-chat", "date": "2025-10-03", "createdAt": "2023-11-29", "sourceUpdatedAt": "2025-10-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT-4 LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping...", "popularity": {"value": 761, "label": "stars"}, "url": "https://github.com/Azure-Samples/contoso-chat", "tags": ["llmops", "rag"]}
{"id": "hf-dataset:gksriharsha/chitralekha", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gksriharsha/chitralekha", "date": "2024-08-23", "createdAt": "2023-11-29", "sourceUpdatedAt": "2024-08-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 146491 downloads.", "popularity": {"value": 146491, "label": "downloads"}, "url": "https://huggingface.co/datasets/gksriharsha/chitralekha", "tags": ["datasets", "doi:10.57967/hf/3403", "format:parquet", "language:te", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:MMMU/MMMU", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "MMMU/MMMU", "date": "2026-04-21", "createdAt": "2023-11-27", "sourceUpdatedAt": "2026-04-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 86897 downloads.", "popularity": {"value": 86897, "label": "downloads"}, "url": "https://huggingface.co/datasets/MMMU/MMMU", "tags": ["accounting", "agriculture", "architecture", "art", "art_theory", "arxiv:2311.16502", "basic_medical_science", "biology"]}
{"id": "hf-dataset:Idavidrein/gpqa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Idavidrein/gpqa", "date": "2026-03-05", "createdAt": "2023-11-27", "sourceUpdatedAt": "2026-03-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 130840 downloads.", "popularity": {"value": 130840, "label": "downloads"}, "url": "https://huggingface.co/datasets/Idavidrein/gpqa", "tags": ["arxiv:2311.12022", "benchmark:eval-yaml", "benchmark:official", "datasets", "format:csv", "language:en", "library:datasets", "library:mlcroissant"]}
{"id": "github:reorproject/reor", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "reorproject/reor", "date": "2025-05-13", "createdAt": "2023-11-27", "sourceUpdatedAt": "2025-05-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Private & local AI personal knowledge management app for high entropy people.", "popularity": {"value": 8562, "label": "stars"}, "url": "https://github.com/reorproject/reor", "tags": ["rag"]}
{"id": "hf-model:stabilityai/sdxl-turbo", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "stabilityai/sdxl-turbo", "date": "2023-11-27", "createdAt": "2023-11-27", "sourceUpdatedAt": "2023-11-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1051492 downloads and tags: diffusers, onnx, safetensors, text-to-image.", "popularity": {"value": 1051492, "label": "downloads"}, "url": "https://huggingface.co/stabilityai/sdxl-turbo", "tags": ["diffusers", "diffusers:stablediffusionxlpipeline", "image-generation", "license:other", "onnx", "region:us", "safetensors", "text-to-image"]}
{"id": "hf-model:stabilityai/sd-turbo", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "stabilityai/sd-turbo", "date": "2023-11-27", "createdAt": "2023-11-27", "sourceUpdatedAt": "2023-11-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 679696 downloads and tags: diffusers, safetensors, text-to-image, diffusers:StableDiffusionPipeline.", "popularity": {"value": 679696, "label": "downloads"}, "url": "https://huggingface.co/stabilityai/sd-turbo", "tags": ["diffusers", "diffusers:stablediffusionpipeline", "image-generation", "region:us", "safetensors", "text-to-image"]}
{"id": "github:mmmu-benchmark/mmmu", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "MMMU-Benchmark/MMMU", "date": "2026-02-12", "createdAt": "2023-11-23", "sourceUpdatedAt": "2026-02-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "This repo contains evaluation code for the paper \"MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI\"", "popularity": {"value": 575, "label": "stars"}, "url": "https://github.com/MMMU-Benchmark/MMMU", "tags": ["evaluation"]}
{"id": "hf-dataset:ylacombe/cml-tts", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ylacombe/cml-tts", "date": "2023-11-24", "createdAt": "2023-11-23", "sourceUpdatedAt": "2023-11-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 79228 downloads.", "popularity": {"value": 79228, "label": "downloads"}, "url": "https://huggingface.co/datasets/ylacombe/cml-tts", "tags": ["arxiv:2306.10097", "datasets", "format:parquet", "language:de", "language:es", "language:fr", "language:it", "language:nl"]}
{"id": "hf-model:Systran/faster-whisper-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Systran/faster-whisper-base", "date": "2023-11-23", "createdAt": "2023-11-23", "sourceUpdatedAt": "2023-11-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1382387 downloads and tags: ctranslate2, audio, automatic-speech-recognition, en.", "popularity": {"value": 1382387, "label": "downloads"}, "url": "https://huggingface.co/Systran/faster-whisper-base", "tags": ["audio", "automatic-speech-recognition", "ctranslate2", "de", "en", "es", "ru", "zh"]}
{"id": "github:yingqinghe/awesome-llms-meet-multimodal-generation", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "YingqingHe/Awesome-LLMs-meet-Multimodal-Generation", "date": "2025-04-04", "createdAt": "2023-11-17", "sourceUpdatedAt": "2025-04-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).", "popularity": {"value": 545, "label": "stars"}, "url": "https://github.com/YingqingHe/Awesome-LLMs-meet-Multimodal-Generation", "tags": ["text-to-image", "video-tools"]}
{"id": "hf-model:jinaai/jina-embeddings-v2-base-code", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jinaai/jina-embeddings-v2-base-code", "date": "2023-11-17", "createdAt": "2023-11-17", "sourceUpdatedAt": "2023-11-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 744847 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 744847, "label": "downloads"}, "url": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", "tags": ["bert", "embeddings", "feature-extraction", "fill-mask", "onnx", "pytorch", "safetensors", "sentence-similarity"]}
{"id": "github:datawhalechina/self-llm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "datawhalechina/self-llm", "date": "2026-06-03", "createdAt": "2023-11-16", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程", "popularity": {"value": 30740, "label": "stars"}, "url": "https://github.com/datawhalechina/self-llm", "tags": ["llm", "tools"]}
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{"id": "github:mintplex-labs/openai-assistant-swarm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Mintplex-Labs/openai-assistant-swarm", "date": "2023-11-18", "createdAt": "2023-11-16", "sourceUpdatedAt": "2023-11-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Introducing the Assistant Swarm. An extension to the OpenAI Node SDK to automatically delegate work to any assistant you create in OpenAi through one united interface and manager. Now you can delegate work to a swarm of assistant all specialized with specif...", "popularity": {"value": 615, "label": "stars"}, "url": "https://github.com/Mintplex-Labs/openai-assistant-swarm", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-model:pyannote/speaker-diarization-3.1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "pyannote/speaker-diarization-3.1", "date": "2023-11-16", "createdAt": "2023-11-16", "sourceUpdatedAt": "2023-11-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 9591508 downloads and tags: pyannote-audio, pyannote, pyannote-audio-pipeline, audio.", "popularity": {"value": 9591508, "label": "downloads"}, "url": "https://huggingface.co/pyannote/speaker-diarization-3.1", "tags": ["audio", "pyannote", "pyannote-audio", "pyannote-audio-pipeline", "speaker", "speaker-diarization", "speech", "voice"]}
{"id": "hf-dataset:locuslab/TOFU", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "locuslab/TOFU", "date": "2025-03-27", "createdAt": "2023-11-14", "sourceUpdatedAt": "2025-03-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 103214 downloads.", "popularity": {"value": 103214, "label": "downloads"}, "url": "https://huggingface.co/datasets/locuslab/TOFU", "tags": ["annotations_creators:machine-generated", "arxiv:2401.06121", "datasets", "format:json", "language:en", "language_creators:machine-generated", "library:datasets", "library:mlcroissant"]}
{"id": "github:neurocult/agency", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "neurocult/agency", "date": "2025-01-08", "createdAt": "2023-11-13", "sourceUpdatedAt": "2025-01-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🕵️‍♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.", "popularity": {"value": 508, "label": "stars"}, "url": "https://github.com/neurocult/agency", "tags": ["tools", "vector-database"]}
{"id": "hf-dataset:fsicoli/common_voice_15_0", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fsicoli/common_voice_15_0", "date": "2023-12-20", "createdAt": "2023-11-13", "sourceUpdatedAt": "2023-12-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 121135 downloads.", "popularity": {"value": 121135, "label": "downloads"}, "url": "https://huggingface.co/datasets/fsicoli/common_voice_15_0", "tags": ["datasets", "foundation", "language:ab", "language:af", "language:am", "language:ar", "language:as", "language:ast"]}
{"id": "hf-model:pyannote/wespeaker-voxceleb-resnet34-LM", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "pyannote/wespeaker-voxceleb-resnet34-LM", "date": "2023-11-13", "createdAt": "2023-11-13", "sourceUpdatedAt": "2023-11-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 9480491 downloads and tags: pyannote-audio, pytorch, pyannote, pyannote-audio-model.", "popularity": {"value": 9480491, "label": "downloads"}, "url": "https://huggingface.co/pyannote/wespeaker-voxceleb-resnet34-LM", "tags": ["audio", "pyannote", "pyannote-audio", "pyannote-audio-model", "pytorch", "speech", "voice", "wespeaker"]}
{"id": "github:anil-matcha/awesome-gpt-image-2-api-prompts", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Anil-matcha/Awesome-GPT-Image-2-API-Prompts", "date": "2026-06-02", "createdAt": "2023-11-10", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Curated GPT-Image-2 prompts for the OpenAI API — portraits, posters, UI mockups, game screenshots, character sheets, and more. Ready-to-use prompts for gpt-image-2.", "popularity": {"value": 2063, "label": "stars"}, "url": "https://github.com/Anil-matcha/Awesome-GPT-Image-2-API-Prompts", "tags": ["text-to-image", "tools"]}
{"id": "github:superlinked/sie", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "superlinked/sie", "date": "2026-06-03", "createdAt": "2023-11-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Superlinked Inference Engine is an Open-source inference server and production cluster for embeddings, reranking, and extraction.", "popularity": {"value": 2023, "label": "stars"}, "url": "https://github.com/superlinked/sie", "tags": ["inference"]}
{"id": "hf-dataset:links-ads/gaia-vineyard-uav-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "links-ads/gaia-vineyard-uav-dataset", "date": "2023-11-20", "createdAt": "2023-11-07", "sourceUpdatedAt": "2023-11-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 58535 downloads.", "popularity": {"value": 58535, "label": "downloads"}, "url": "https://huggingface.co/datasets/links-ads/gaia-vineyard-uav-dataset", "tags": ["datasets", "modality:image", "region:us"]}
{"id": "hf-model:openai/whisper-large-v3", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/whisper-large-v3", "date": "2023-11-07", "createdAt": "2023-11-07", "sourceUpdatedAt": "2023-11-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5348543 downloads and tags: transformers, pytorch, jax, safetensors.", "popularity": {"value": 5348543, "label": "downloads"}, "url": "https://huggingface.co/openai/whisper-large-v3", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "jax", "pytorch", "safetensors", "transformers", "whisper"]}
{"id": "hf-dataset:ppxscal/arxiv-metadata-oai-snapshot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ppxscal/arxiv-metadata-oai-snapshot", "date": "2023-11-07", "createdAt": "2023-11-07", "sourceUpdatedAt": "2023-11-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49519 downloads.", "popularity": {"value": 49519, "label": "downloads"}, "url": "https://huggingface.co/datasets/ppxscal/arxiv-metadata-oai-snapshot", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:text", "region:us"]}
{"id": "github:garibida/cross-image-attention", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "garibida/cross-image-attention", "date": "2024-05-05", "createdAt": "2023-11-04", "sourceUpdatedAt": "2024-05-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Officail Implementation for \"Cross-Image Attention for Zero-Shot Appearance Transfer\"", "popularity": {"value": 403, "label": "stars"}, "url": "https://github.com/garibida/cross-image-attention", "tags": ["text-to-image", "tools"]}
{"id": "github:pytorch/ao", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pytorch/ao", "date": "2026-06-03", "createdAt": "2023-11-03", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "PyTorch native quantization and sparsity for training and inference", "popularity": {"value": 2843, "label": "stars"}, "url": "https://github.com/pytorch/ao", "tags": ["inference"]}
{"id": "hf-dataset:gaia-benchmark/results_public", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gaia-benchmark/results_public", "date": "2026-06-04", "createdAt": "2023-10-31", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54194 downloads.", "popularity": {"value": 54194, "label": "downloads"}, "url": "https://huggingface.co/datasets/gaia-benchmark/results_public", "tags": ["datasets", "format:optimized-parquet", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular"]}
{"id": "github:vectara/hallucination-leaderboard", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vectara/hallucination-leaderboard", "date": "2026-05-11", "createdAt": "2023-10-31", "sourceUpdatedAt": "2026-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents", "popularity": {"value": 3271, "label": "stars"}, "url": "https://github.com/vectara/hallucination-leaderboard", "tags": ["evaluation", "generative-ai"]}
{"id": "hf-dataset:hails/mmlu_no_train", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hails/mmlu_no_train", "date": "2025-07-13", "createdAt": "2023-10-31", "sourceUpdatedAt": "2025-07-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 65570 downloads.", "popularity": {"value": 65570, "label": "downloads"}, "url": "https://huggingface.co/datasets/hails/mmlu_no_train", "tags": ["datasets", "language:en", "license:mit", "modality:text", "region:us", "size_categories:10k<n<100k", "task_categories:question-answering"]}
{"id": "hf-model:coqui/XTTS-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "coqui/XTTS-v2", "date": "2023-10-31", "createdAt": "2023-10-31", "sourceUpdatedAt": "2023-10-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 9945695 downloads and tags: coqui, text-to-speech, license:other, region:us.", "popularity": {"value": 9945695, "label": "downloads"}, "url": "https://huggingface.co/coqui/XTTS-v2", "tags": ["audio", "coqui", "license:other", "region:us", "text-to-speech"]}
{"id": "github:aurelio-labs/semantic-router", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "aurelio-labs/semantic-router", "date": "2026-05-23", "createdAt": "2023-10-30", "sourceUpdatedAt": "2026-05-23", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Superfast AI decision making and intelligent processing of multi-modal data.", "popularity": {"value": 3576, "label": "stars"}, "url": "https://github.com/aurelio-labs/semantic-router", "tags": ["generative-ai", "tools"]}
{"id": "github:datawhalechina/llm-universe", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "datawhalechina/llm-universe", "date": "2026-02-24", "createdAt": "2023-10-29", "sourceUpdatedAt": "2026-02-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/", "popularity": {"value": 13181, "label": "stars"}, "url": "https://github.com/datawhalechina/llm-universe", "tags": ["rag"]}
{"id": "github:crewaiinc/crewai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "crewAIInc/crewAI", "date": "2026-06-04", "createdAt": "2023-10-27", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.", "popularity": {"value": 52787, "label": "stars"}, "url": "https://github.com/crewAIInc/crewAI", "tags": ["agents", "ai", "ai-agents", "aiagentframework", "llms"]}
{"id": "github:plandex-ai/plandex", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "plandex-ai/plandex", "date": "2025-10-03", "createdAt": "2023-10-24", "sourceUpdatedAt": "2025-10-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open source AI coding agent. Designed for large projects and real world tasks.", "popularity": {"value": 15438, "label": "stars"}, "url": "https://github.com/plandex-ai/plandex", "tags": ["agents", "ai-tools"]}
{"id": "hf-dataset:HuggingFaceH4/ultrachat_200k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "HuggingFaceH4/ultrachat_200k", "date": "2024-10-16", "createdAt": "2023-10-24", "sourceUpdatedAt": "2024-10-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 69467 downloads.", "popularity": {"value": 69467, "label": "downloads"}, "url": "https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k", "tags": ["arxiv:2305.14233", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:atom-in-the-universe/cc-doc-links", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "atom-in-the-universe/cc-doc-links", "date": "2023-10-26", "createdAt": "2023-10-24", "sourceUpdatedAt": "2023-10-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 110925 downloads.", "popularity": {"value": 110925, "label": "downloads"}, "url": "https://huggingface.co/datasets/atom-in-the-universe/cc-doc-links", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:atom-in-the-universe/cc-pdf-links", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "atom-in-the-universe/cc-pdf-links", "date": "2023-10-26", "createdAt": "2023-10-24", "sourceUpdatedAt": "2023-10-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50412 downloads.", "popularity": {"value": 50412, "label": "downloads"}, "url": "https://huggingface.co/datasets/atom-in-the-universe/cc-pdf-links", "tags": ["datasets", "region:us"]}
{"id": "github:predibase/lorax", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "predibase/lorax", "date": "2026-05-28", "createdAt": "2023-10-20", "sourceUpdatedAt": "2026-05-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs", "popularity": {"value": 3788, "label": "stars"}, "url": "https://github.com/predibase/lorax", "tags": ["inference", "llmops"]}
{"id": "hf-dataset:gaia-benchmark/GAIA", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "gaia-benchmark/GAIA", "date": "2025-10-28", "createdAt": "2023-10-20", "sourceUpdatedAt": "2025-10-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50570 downloads.", "popularity": {"value": 50570, "label": "downloads"}, "url": "https://huggingface.co/datasets/gaia-benchmark/GAIA", "tags": ["arxiv:2311.12983", "datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:sebastiandizon/genius-song-lyrics", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sebastiandizon/genius-song-lyrics", "date": "2023-10-20", "createdAt": "2023-10-20", "sourceUpdatedAt": "2023-10-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73918 downloads.", "popularity": {"value": 73918, "label": "downloads"}, "url": "https://huggingface.co/datasets/sebastiandizon/genius-song-lyrics", "tags": ["datasets", "format:csv", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular", "modality:text"]}
{"id": "hf-dataset:common-canvas/commoncatalog-cc-by-nc-sa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "common-canvas/commoncatalog-cc-by-nc-sa", "date": "2024-05-16", "createdAt": "2023-10-19", "sourceUpdatedAt": "2024-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67077 downloads.", "popularity": {"value": 67077, "label": "downloads"}, "url": "https://huggingface.co/datasets/common-canvas/commoncatalog-cc-by-nc-sa", "tags": ["arxiv:2310.16825", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant", "library:polars"]}
{"id": "hf-dataset:Cnam-LMSSC/vibravox", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Cnam-LMSSC/vibravox", "date": "2025-11-07", "createdAt": "2023-10-18", "sourceUpdatedAt": "2025-11-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 53482 downloads.", "popularity": {"value": 53482, "label": "downloads"}, "url": "https://huggingface.co/datasets/Cnam-LMSSC/vibravox", "tags": ["annotations_creators:expert-generated", "arxiv:2006.11477", "arxiv:2303.10008", "arxiv:2401.08342", "arxiv:2407.11828", "datasets", "doi:10.57967/hf/2727", "format:parquet"]}
{"id": "github:pchunduri6/rag-demystified", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pchunduri6/rag-demystified", "date": "2024-01-26", "createdAt": "2023-10-18", "sourceUpdatedAt": "2024-01-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "An LLM-powered advanced RAG pipeline built from scratch", "popularity": {"value": 859, "label": "stars"}, "url": "https://github.com/pchunduri6/rag-demystified", "tags": ["rag", "vector-database"]}
{"id": "github:wethinkin/aigc-interview-book", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "WeThinkIn/AIGC-Interview-Book", "date": "2026-06-03", "createdAt": "2023-10-14", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试秘籍。涵盖AIGC、LLM大模型、AI Agent、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、大数据挖掘、具身智能、元宇宙、AGI等AI行业面试笔试干货经验与核心知识。", "popularity": {"value": 3853, "label": "stars"}, "url": "https://github.com/WeThinkIn/AIGC-Interview-Book", "tags": ["agents", "ai-agent"]}
{"id": "github:letta-ai/letta", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "letta-ai/letta", "date": "2026-05-14", "createdAt": "2023-10-11", "sourceUpdatedAt": "2026-05-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve over time.", "popularity": {"value": 23126, "label": "stars"}, "url": "https://github.com/letta-ai/letta", "tags": ["agents", "llm"]}
{"id": "hf-dataset:librarian-bots/arxiv-metadata-snapshot", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "librarian-bots/arxiv-metadata-snapshot", "date": "2026-06-01", "createdAt": "2023-10-08", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 361920 downloads.", "popularity": {"value": 361920, "label": "downloads"}, "url": "https://huggingface.co/datasets/librarian-bots/arxiv-metadata-snapshot", "tags": ["arxiv", "datasets", "format:optimized-parquet", "format:parquet", "language:en", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "github:open-webui/open-webui", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "open-webui/open-webui", "date": "2026-06-04", "createdAt": "2023-10-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "User-friendly AI Interface (Supports Ollama, OpenAI API, ...)", "popularity": {"value": 139895, "label": "stars"}, "url": "https://github.com/open-webui/open-webui", "tags": ["ai", "llm", "llm-ui", "llm-webui", "llms", "mcp", "ui-demo"]}
{"id": "github:adithya-s-k/ai-engineering.academy", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "adithya-s-k/AI-Engineering.academy", "date": "2026-02-27", "createdAt": "2023-10-05", "sourceUpdatedAt": "2026-02-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Mastering Applied AI, One Concept at a Time", "popularity": {"value": 2210, "label": "stars"}, "url": "https://github.com/adithya-s-k/AI-Engineering.academy", "tags": ["inference"]}
{"id": "hf-dataset:hf-vision/course-assets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-vision/course-assets", "date": "2025-01-24", "createdAt": "2023-10-02", "sourceUpdatedAt": "2025-01-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 116689 downloads.", "popularity": {"value": 116689, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-vision/course-assets", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-model:microsoft/kosmos-2-patch14-224", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/kosmos-2-patch14-224", "date": "2023-10-02", "createdAt": "2023-10-02", "sourceUpdatedAt": "2023-10-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 164069 downloads and tags: transformers, pytorch, safetensors, kosmos-2.", "popularity": {"value": 164069, "label": "downloads"}, "url": "https://huggingface.co/microsoft/kosmos-2-patch14-224", "tags": ["image-captioning", "image-text-to-text", "image-to-text", "kosmos-2", "license:mit", "multimodal", "pytorch", "safetensors"]}
{"id": "hf-model:jinaai/jina-embeddings-v2-small-en", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jinaai/jina-embeddings-v2-small-en", "date": "2023-09-27", "createdAt": "2023-09-27", "sourceUpdatedAt": "2023-09-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1006449 downloads and tags: sentence-transformers, pytorch, coreml, onnx.", "popularity": {"value": 1006449, "label": "downloads"}, "url": "https://huggingface.co/jinaai/jina-embeddings-v2-small-en", "tags": ["bert", "coreml", "embeddings", "feature-extraction", "onnx", "pytorch", "safetensors", "sentence-similarity"]}
{"id": "github:microsoft/aici", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "microsoft/aici", "date": "2025-01-22", "createdAt": "2023-09-26", "sourceUpdatedAt": "2025-01-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AICI: Prompts as (Wasm) Programs", "popularity": {"value": 2076, "label": "stars"}, "url": "https://github.com/microsoft/aici", "tags": ["inference"]}
{"id": "github:viddexa/autollm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "viddexa/autollm", "date": "2024-01-29", "createdAt": "2023-09-21", "sourceUpdatedAt": "2024-01-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Ship RAG based LLM web apps in seconds.", "popularity": {"value": 1004, "label": "stars"}, "url": "https://github.com/viddexa/autollm", "tags": ["rag", "vector-database"]}
{"id": "hf-dataset:meta-math/MetaMathQA", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "meta-math/MetaMathQA", "date": "2023-12-21", "createdAt": "2023-09-21", "sourceUpdatedAt": "2023-12-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 61410 downloads.", "popularity": {"value": 61410, "label": "downloads"}, "url": "https://huggingface.co/datasets/meta-math/MetaMathQA", "tags": ["arxiv:2309.12284", "datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit"]}
{"id": "hf-model:facebook/nougat-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "facebook/nougat-base", "date": "2023-09-21", "createdAt": "2023-09-21", "sourceUpdatedAt": "2023-09-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 302138 downloads and tags: transformers, pytorch, safetensors, vision-encoder-decoder.", "popularity": {"value": 302138, "label": "downloads"}, "url": "https://huggingface.co/facebook/nougat-base", "tags": ["coding", "image-text-to-text", "image-to-text", "nougat", "pytorch", "safetensors", "transformers", "vision"]}
{"id": "github:xnhyacinth/awesome-llm-long-context-modeling", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Xnhyacinth/Awesome-LLM-Long-Context-Modeling", "date": "2026-06-03", "createdAt": "2023-09-17", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "📰 Must-read papers and blogs on LLM based Long Context Modeling 🔥", "popularity": {"value": 2111, "label": "stars"}, "url": "https://github.com/Xnhyacinth/Awesome-LLM-Long-Context-Modeling", "tags": ["evaluation"]}
{"id": "github:1panel-dev/maxkb", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "1Panel-dev/MaxKB", "date": "2026-06-04", "createdAt": "2023-09-14", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🔥 MaxKB is an open-source platform for building enterprise-grade agents.  强大易用的开源企业级智能体平台。", "popularity": {"value": 21137, "label": "stars"}, "url": "https://github.com/1Panel-dev/MaxKB", "tags": ["agents", "rag"]}
{"id": "hf-dataset:EleutherAI/hendrycks_math", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "EleutherAI/hendrycks_math", "date": "2025-01-12", "createdAt": "2023-09-14", "sourceUpdatedAt": "2025-01-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 163338 downloads.", "popularity": {"value": 163338, "label": "downloads"}, "url": "https://huggingface.co/datasets/EleutherAI/hendrycks_math", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:mit", "modality:text"]}
{"id": "github:neumtry/neumai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "NeumTry/NeumAI", "date": "2024-01-15", "createdAt": "2023-09-14", "sourceUpdatedAt": "2024-01-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.", "popularity": {"value": 865, "label": "stars"}, "url": "https://github.com/NeumTry/NeumAI", "tags": ["tools", "vector-database"]}
{"id": "github:google/break-a-scene", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "google/break-a-scene", "date": "2024-01-14", "createdAt": "2023-09-13", "sourceUpdatedAt": "2024-01-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official implementation for \"Break-A-Scene: Extracting Multiple Concepts from a Single Image\" [SIGGRAPH Asia 2023]", "popularity": {"value": 525, "label": "stars"}, "url": "https://github.com/google/break-a-scene", "tags": ["text-to-image", "tools"]}
{"id": "hf-model:Xenova/bge-base-en-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Xenova/bge-base-en-v1.5", "date": "2023-09-13", "createdAt": "2023-09-13", "sourceUpdatedAt": "2023-09-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1756243 downloads and tags: transformers.js, onnx, bert, feature-extraction.", "popularity": {"value": 1756243, "label": "downloads"}, "url": "https://huggingface.co/Xenova/bge-base-en-v1.5", "tags": ["base_model:baai/bge-base-en-v1.5", "base_model:quantized:baai/bge-base-en-v1.5", "bert", "embeddings", "feature-extraction", "license:mit", "onnx", "region:us"]}
{"id": "hf-model:BAAI/bge-small-en-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-small-en-v1.5", "date": "2023-09-12", "createdAt": "2023-09-12", "sourceUpdatedAt": "2023-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 54972503 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 54972503, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-small-en-v1.5", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "pytorch", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "hf-model:BAAI/bge-large-en-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-large-en-v1.5", "date": "2023-09-12", "createdAt": "2023-09-12", "sourceUpdatedAt": "2023-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 15396003 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 15396003, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-large-en-v1.5", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "pytorch", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "hf-model:BAAI/bge-small-zh-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-small-zh-v1.5", "date": "2023-09-12", "createdAt": "2023-09-12", "sourceUpdatedAt": "2023-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3535287 downloads and tags: transformers, pytorch, safetensors, bert.", "popularity": {"value": 3535287, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-small-zh-v1.5", "tags": ["arxiv:2309.07597", "arxiv:2310.07554", "bert", "embeddings", "feature-extraction", "pytorch", "safetensors", "transformers"]}
{"id": "hf-model:BAAI/bge-reranker-large", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-reranker-large", "date": "2023-09-12", "createdAt": "2023-09-12", "sourceUpdatedAt": "2023-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1575485 downloads and tags: transformers, pytorch, onnx, safetensors.", "popularity": {"value": 1575485, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-reranker-large", "tags": ["embeddings", "feature-extraction", "mteb", "onnx", "pytorch", "safetensors", "text-classification", "transformers"]}
{"id": "hf-model:BAAI/bge-large-zh-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-large-zh-v1.5", "date": "2023-09-12", "createdAt": "2023-09-12", "sourceUpdatedAt": "2023-09-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1077725 downloads and tags: sentence-transformers, pytorch, bert, feature-extraction.", "popularity": {"value": 1077725, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-large-zh-v1.5", "tags": ["arxiv:2401.03462", "bert", "embeddings", "feature-extraction", "pytorch", "sentence-similarity", "sentence-transformers", "transformers"]}
{"id": "hf-model:BAAI/bge-base-en-v1.5", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "BAAI/bge-base-en-v1.5", "date": "2023-09-11", "createdAt": "2023-09-11", "sourceUpdatedAt": "2023-09-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 9465131 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 9465131, "label": "downloads"}, "url": "https://huggingface.co/BAAI/bge-base-en-v1.5", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "pytorch", "safetensors", "sentence-similarity", "sentence-transformers"]}
{"id": "github:plastic-labs/honcho", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "plastic-labs/honcho", "date": "2026-06-02", "createdAt": "2023-09-10", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Memory library for building stateful agents", "popularity": {"value": 4735, "label": "stars"}, "url": "https://github.com/plastic-labs/honcho", "tags": ["agents", "vector-database"]}
{"id": "github:tairov/llama2.mojo", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "tairov/llama2.mojo", "date": "2026-02-09", "createdAt": "2023-09-10", "sourceUpdatedAt": "2026-02-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Inference Llama 2 in one file of pure 🔥", "popularity": {"value": 2124, "label": "stars"}, "url": "https://github.com/tairov/llama2.mojo", "tags": ["inference"]}
{"id": "github:langwatch/langwatch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "langwatch/langwatch", "date": "2026-06-04", "createdAt": "2023-09-09", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The platform for LLM evaluations and AI agent testing", "popularity": {"value": 3285, "label": "stars"}, "url": "https://github.com/langwatch/langwatch", "tags": ["agents", "llmops"]}
{"id": "github:traceloop/openllmetry", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "traceloop/openllmetry", "date": "2026-06-04", "createdAt": "2023-09-02", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source observability for your GenAI or LLM application, based on OpenTelemetry", "popularity": {"value": 7170, "label": "stars"}, "url": "https://github.com/traceloop/openllmetry", "tags": ["llmops", "tools"]}
{"id": "github:acly/krita-ai-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Acly/krita-ai-diffusion", "date": "2026-06-03", "createdAt": "2023-09-01", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Streamlined interface for generating images with AI in Krita. Inpaint and outpaint with optional text prompt, no tweaking required.", "popularity": {"value": 10158, "label": "stars"}, "url": "https://github.com/Acly/krita-ai-diffusion", "tags": ["generative-ai", "tools"]}
{"id": "hf-dataset:facebook/belebele", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "facebook/belebele", "date": "2024-08-12", "createdAt": "2023-09-01", "sourceUpdatedAt": "2024-08-12", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 47888 downloads.", "popularity": {"value": 47888, "label": "downloads"}, "url": "https://huggingface.co/datasets/facebook/belebele", "tags": ["datasets", "format:json", "language:af", "language:am", "language:ar", "language:as", "language:az", "language:bg"]}
{"id": "hf-model:facebook/mms-tts-hat", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "facebook/mms-tts-hat", "date": "2023-09-01", "createdAt": "2023-09-01", "sourceUpdatedAt": "2023-09-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 457575 downloads and tags: transformers, pytorch, safetensors, vits.", "popularity": {"value": 457575, "label": "downloads"}, "url": "https://huggingface.co/facebook/mms-tts-hat", "tags": ["arxiv:2305.13516", "audio", "mms", "pytorch", "safetensors", "text-to-audio", "text-to-speech", "transformers"]}
{"id": "hf-model:diffusers/stable-diffusion-xl-1.0-inpainting-0.1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "diffusers/stable-diffusion-xl-1.0-inpainting-0.1", "date": "2023-09-01", "createdAt": "2023-09-01", "sourceUpdatedAt": "2023-09-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 279298 downloads and tags: diffusers, safetensors, stable-diffusion-xl, stable-diffusion-xl-diffusers.", "popularity": {"value": 279298, "label": "downloads"}, "url": "https://huggingface.co/diffusers/stable-diffusion-xl-1.0-inpainting-0.1", "tags": ["arxiv:2112.10752", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "diffusers", "image-generation", "inpainting", "safetensors", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"]}
{"id": "hf-dataset:monology/pile-uncopyrighted", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "monology/pile-uncopyrighted", "date": "2023-08-31", "createdAt": "2023-08-30", "sourceUpdatedAt": "2023-08-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73142 downloads.", "popularity": {"value": 73142, "label": "downloads"}, "url": "https://huggingface.co/datasets/monology/pile-uncopyrighted", "tags": ["arxiv:2101.00027", "datasets", "format:json", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "license:other"]}
{"id": "hf-dataset:jat-project/jat-dataset", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "jat-project/jat-dataset", "date": "2024-02-16", "createdAt": "2023-08-29", "sourceUpdatedAt": "2024-02-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 733713 downloads.", "popularity": {"value": 733713, "label": "downloads"}, "url": "https://huggingface.co/datasets/jat-project/jat-dataset", "tags": ["annotations_creators:found", "annotations_creators:machine-generated", "arxiv:2303.03915", "arxiv:2402.09844", "datasets", "format:parquet", "generalist-agent", "imitation-learning"]}
{"id": "github:dataelement/bisheng", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dataelement/bisheng", "date": "2026-06-03", "createdAt": "2023-08-28", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management...", "popularity": {"value": 11427, "label": "stars"}, "url": "https://github.com/dataelement/bisheng", "tags": ["agents", "rag"]}
{"id": "github:ai-for-developers/awesome-vibe-coding", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ai-for-developers/awesome-vibe-coding", "date": "2026-04-18", "createdAt": "2023-08-28", "sourceUpdatedAt": "2026-04-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A hand-picked collection of tools and resources for Vibe Coding", "popularity": {"value": 733, "label": "stars"}, "url": "https://github.com/ai-for-developers/awesome-vibe-coding", "tags": ["ai-tools", "developer-tools"]}
{"id": "github:liguodongiot/llm-resource", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "liguodongiot/llm-resource", "date": "2025-07-15", "createdAt": "2023-08-27", "sourceUpdatedAt": "2025-07-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LLM全栈优质资源汇总", "popularity": {"value": 716, "label": "stars"}, "url": "https://github.com/liguodongiot/llm-resource", "tags": ["llmops", "tools"]}
{"id": "hf-model:Lykon/dreamshaper-7", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Lykon/dreamshaper-7", "date": "2023-08-26", "createdAt": "2023-08-26", "sourceUpdatedAt": "2023-08-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 247249 downloads and tags: diffusers, safetensors, stable-diffusion, stable-diffusion-diffusers.", "popularity": {"value": 247249, "label": "downloads"}, "url": "https://huggingface.co/Lykon/dreamshaper-7", "tags": ["anime", "art", "artistic", "diffusers", "image-generation", "safetensors", "stable-diffusion", "stable-diffusion-diffusers"]}
{"id": "github:mahseema/awesome-ai-tools", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mahseema/awesome-ai-tools", "date": "2025-12-31", "createdAt": "2023-08-25", "sourceUpdatedAt": "2025-12-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of Artificial Intelligence Top Tools", "popularity": {"value": 5389, "label": "stars"}, "url": "https://github.com/mahseema/awesome-ai-tools", "tags": ["agents", "ai-agent"]}
{"id": "hf-dataset:hf-internal-testing/imagefolder_with_metadata", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/imagefolder_with_metadata", "date": "2025-03-04", "createdAt": "2023-08-24", "sourceUpdatedAt": "2025-03-04", "lastSeenAt": "2026-06-02T03:03:42+00:00", "summary": "Hugging Face dataset with 46575 downloads.", "popularity": {"value": 46575, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/imagefolder_with_metadata", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:hf-internal-testing/dataset_with_data_files", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/dataset_with_data_files", "date": "2024-09-05", "createdAt": "2023-08-24", "sourceUpdatedAt": "2024-09-05", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47316 downloads.", "popularity": {"value": 47316, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/dataset_with_data_files", "tags": ["datasets", "format:text", "library:datasets", "library:mlcroissant", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:hf-internal-testing/dataset_with_script", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/dataset_with_script", "date": "2024-08-24", "createdAt": "2023-08-24", "sourceUpdatedAt": "2024-08-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66235 downloads.", "popularity": {"value": 66235, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/dataset_with_script", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:hf-internal-testing/audiofolder_two_configs_in_metadata", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/audiofolder_two_configs_in_metadata", "date": "2023-06-02", "createdAt": "2023-08-24", "sourceUpdatedAt": "2023-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66587 downloads.", "popularity": {"value": 66587, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/audiofolder_two_configs_in_metadata", "tags": ["datasets", "format:audiofolder", "library:datasets", "library:mlcroissant", "modality:audio", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:hf-internal-testing/audiofolder_single_config_in_metadata", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/audiofolder_single_config_in_metadata", "date": "2023-06-02", "createdAt": "2023-08-24", "sourceUpdatedAt": "2023-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51638 downloads.", "popularity": {"value": 51638, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/audiofolder_single_config_in_metadata", "tags": ["datasets", "format:audiofolder", "library:datasets", "library:mlcroissant", "modality:audio", "region:us", "size_categories:n<1k"]}
{"id": "github:portkey-ai/gateway", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Portkey-AI/gateway", "date": "2026-05-25", "createdAt": "2023-08-23", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.", "popularity": {"value": 11959, "label": "stars"}, "url": "https://github.com/Portkey-AI/gateway", "tags": ["llmops", "tools"]}
{"id": "github:superlinked/vectorhub", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "superlinked/VectorHub", "date": "2026-06-01", "createdAt": "2023-08-21", "sourceUpdatedAt": "2026-06-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "VectorHub is a free, open-source learning website for people (software developers to senior ML architects) interested in adding vector retrieval to their ML stack.", "popularity": {"value": 522, "label": "stars"}, "url": "https://github.com/superlinked/VectorHub", "tags": ["rag", "vector-database"]}
{"id": "github:microsoft/autogen", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "microsoft/autogen", "date": "2026-04-15", "createdAt": "2023-08-18", "sourceUpdatedAt": "2026-04-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A programming framework for agentic AI", "popularity": {"value": 58673, "label": "stars"}, "url": "https://github.com/microsoft/autogen", "tags": ["agentic", "agentic-agi", "agents", "ai", "autogen", "autogen-ecosystem"]}
{"id": "github:janhq/jan", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "janhq/jan", "date": "2026-06-02", "createdAt": "2023-08-17", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.", "popularity": {"value": 42842, "label": "stars"}, "url": "https://github.com/janhq/jan", "tags": ["llm", "tools"]}
{"id": "github:topoteretes/cognee", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "topoteretes/cognee", "date": "2026-06-03", "createdAt": "2023-08-16", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Memory platform for AI Agents in 6 lines of code", "popularity": {"value": 17662, "label": "stars"}, "url": "https://github.com/topoteretes/cognee", "tags": ["agents", "rag"]}
{"id": "hf-dataset:glaiveai/glaive-function-calling-v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "glaiveai/glaive-function-calling-v2", "date": "2023-09-27", "createdAt": "2023-08-15", "sourceUpdatedAt": "2023-09-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 66015 downloads.", "popularity": {"value": 66015, "label": "downloads"}, "url": "https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2", "tags": ["datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:apache-2.0"]}
{"id": "hf-dataset:rtrm/debug", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rtrm/debug", "date": "2023-08-14", "createdAt": "2023-08-11", "sourceUpdatedAt": "2023-08-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 193750 downloads.", "popularity": {"value": 193750, "label": "downloads"}, "url": "https://huggingface.co/datasets/rtrm/debug", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:confident-ai/deepeval", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "confident-ai/deepeval", "date": "2026-06-03", "createdAt": "2023-08-10", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The LLM Evaluation Framework", "popularity": {"value": 15899, "label": "stars"}, "url": "https://github.com/confident-ai/deepeval", "tags": ["evaluation", "evaluation-framework", "evaluation-metrics", "llm-evaluation", "llm-evaluation-framework", "llm-evaluation-metrics", "python"]}
{"id": "github:langchain-ai/langgraph", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "langchain-ai/langgraph", "date": "2026-06-04", "createdAt": "2023-08-09", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Build resilient agents.", "popularity": {"value": 33788, "label": "stars"}, "url": "https://github.com/langchain-ai/langgraph", "tags": ["agents", "ai", "ai-agents", "chatgpt", "deepagents", "enterprise"]}
{"id": "github:pinecone-io/canopy", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pinecone-io/canopy", "date": "2024-11-13", "createdAt": "2023-08-08", "sourceUpdatedAt": "2024-11-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone", "popularity": {"value": 1033, "label": "stars"}, "url": "https://github.com/pinecone-io/canopy", "tags": ["rag", "vector-database"]}
{"id": "github:dot-agent/nextpy", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dot-agent/nextpy", "date": "2024-05-01", "createdAt": "2023-08-07", "sourceUpdatedAt": "2024-05-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🤖Self-Modifying Framework from the Future 🔮 World's First AMS", "popularity": {"value": 2336, "label": "stars"}, "url": "https://github.com/dot-agent/nextpy", "tags": ["llmops", "ui-demo"]}
{"id": "github:trypromptly/llmstack", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "trypromptly/LLMStack", "date": "2024-12-11", "createdAt": "2023-08-06", "sourceUpdatedAt": "2024-12-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "No-code multi-agent framework to build LLM Agents, workflows and applications with your data", "popularity": {"value": 2303, "label": "stars"}, "url": "https://github.com/trypromptly/LLMStack", "tags": ["agents", "llmops"]}
{"id": "github:e2b-dev/awesome-ai-sdks", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "e2b-dev/awesome-ai-sdks", "date": "2025-02-26", "createdAt": "2023-08-05", "sourceUpdatedAt": "2025-02-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A database of SDKs, frameworks, libraries, and tools for creating, monitoring, debugging and deploying autonomous AI agents", "popularity": {"value": 1179, "label": "stars"}, "url": "https://github.com/e2b-dev/awesome-ai-sdks", "tags": ["agents", "llmops"]}
{"id": "github:finegrain-ai/refiners", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "finegrain-ai/refiners", "date": "2025-09-17", "createdAt": "2023-08-04", "sourceUpdatedAt": "2025-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A microframework on top of PyTorch with first-class citizen APIs for foundation model adaptation", "popularity": {"value": 834, "label": "stars"}, "url": "https://github.com/finegrain-ai/refiners", "tags": ["text-to-image", "tools"]}
{"id": "github:roboflow/inference", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "roboflow/inference", "date": "2026-06-04", "createdAt": "2023-07-31", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Turn any computer or edge device into a command center for your computer vision projects.", "popularity": {"value": 2296, "label": "stars"}, "url": "https://github.com/roboflow/inference", "tags": ["inference"]}
{"id": "github:llphant/llphant", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "LLPhant/LLPhant", "date": "2026-05-16", "createdAt": "2023-07-31", "sourceUpdatedAt": "2026-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LLPhant - A comprehensive PHP Generative AI Framework using OpenAI GPT 4. Inspired by Langchain", "popularity": {"value": 1682, "label": "stars"}, "url": "https://github.com/LLPhant/LLPhant", "tags": ["tools", "vector-database"]}
{"id": "hf-model:SG161222/Realistic_Vision_V5.1_noVAE", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "SG161222/Realistic_Vision_V5.1_noVAE", "date": "2023-07-31", "createdAt": "2023-07-31", "sourceUpdatedAt": "2023-07-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 579912 downloads and tags: diffusers, safetensors, license:creativeml-openrail-m, endpoints_compatible.", "popularity": {"value": 579912, "label": "downloads"}, "url": "https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE", "tags": ["diffusers", "diffusers:stablediffusionpipeline", "endpoints_compatible", "image-generation", "license:creativeml-openrail-m", "region:us", "safetensors"]}
{"id": "hf-dataset:ArmelR/the-pile-splitted", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ArmelR/the-pile-splitted", "date": "2023-09-06", "createdAt": "2023-07-30", "sourceUpdatedAt": "2023-09-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55018 downloads.", "popularity": {"value": 55018, "label": "downloads"}, "url": "https://huggingface.co/datasets/ArmelR/the-pile-splitted", "tags": ["arxiv:2101.00027", "arxiv:2201.07311", "datasets", "format:arrow", "library:datasets", "library:mlcroissant", "modality:text", "region:us"]}
{"id": "hf-dataset:zai-org/LongBench", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "zai-org/LongBench", "date": "2024-12-18", "createdAt": "2023-07-29", "sourceUpdatedAt": "2024-12-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73987 downloads.", "popularity": {"value": 73987, "label": "downloads"}, "url": "https://huggingface.co/datasets/zai-org/LongBench", "tags": ["arxiv:1712.07040", "arxiv:1910.10683", "arxiv:2104.02112", "arxiv:2104.05938", "arxiv:2105.03011", "arxiv:2108.00573", "arxiv:2303.09752", "arxiv:2305.05280"]}
{"id": "github:berriai/litellm", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "BerriAI/litellm", "date": "2026-06-04", "createdAt": "2023-07-27", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM]", "popularity": {"value": 49207, "label": "stars"}, "url": "https://github.com/BerriAI/litellm", "tags": ["inference", "llm"]}
{"id": "github:protectai/llm-guard", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "protectai/llm-guard", "date": "2025-12-15", "createdAt": "2023-07-27", "sourceUpdatedAt": "2025-12-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The Security Toolkit for LLM Interactions", "popularity": {"value": 3033, "label": "stars"}, "url": "https://github.com/protectai/llm-guard", "tags": ["developer-tools", "llmops"]}
{"id": "hf-model:segmind/small-sd", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "segmind/small-sd", "date": "2023-07-27", "createdAt": "2023-07-27", "sourceUpdatedAt": "2023-07-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 228157 downloads and tags: diffusers, stable-diffusion, stable-diffusion-diffusers, text-to-image.", "popularity": {"value": 228157, "label": "downloads"}, "url": "https://huggingface.co/segmind/small-sd", "tags": ["arxiv:2305.15798", "base_model:finetune:sg161222/realistic_vision_v4.0_novae", "base_model:sg161222/realistic_vision_v4.0_novae", "dataset:recastai/laion-art-en-improved-captions", "diffusers", "image-generation", "stable-diffusion", "stable-diffusion-diffusers"]}
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{"id": "hf-dataset:lavita/medical-qa-shared-task-v1-toy", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lavita/medical-qa-shared-task-v1-toy", "date": "2023-07-20", "createdAt": "2023-07-20", "sourceUpdatedAt": "2023-07-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 195334 downloads.", "popularity": {"value": 195334, "label": "downloads"}, "url": "https://huggingface.co/datasets/lavita/medical-qa-shared-task-v1-toy", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular", "modality:text"]}
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{"id": "hf-dataset:lmsys/chatbot_arena_conversations", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lmsys/chatbot_arena_conversations", "date": "2023-09-30", "createdAt": "2023-07-18", "sourceUpdatedAt": "2023-09-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 87767 downloads.", "popularity": {"value": 87767, "label": "downloads"}, "url": "https://huggingface.co/datasets/lmsys/chatbot_arena_conversations", "tags": ["arxiv:2306.05685", "datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:cc"]}
{"id": "hf-dataset:UniverseTBD/arxiv-abstracts-large", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "UniverseTBD/arxiv-abstracts-large", "date": "2023-07-18", "createdAt": "2023-07-18", "sourceUpdatedAt": "2023-07-18", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 47396 downloads.", "popularity": {"value": 47396, "label": "downloads"}, "url": "https://huggingface.co/datasets/UniverseTBD/arxiv-abstracts-large", "tags": ["datasets", "format:json", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "license:afl-3.0"]}
{"id": "github:theodo-group/genossgpt", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "theodo-group/GenossGPT", "date": "2023-12-15", "createdAt": "2023-07-16", "sourceUpdatedAt": "2023-12-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "One API for all LLMs either Private or Public (Anthropic, Llama V2, GPT 3.5/4, Vertex, GPT4ALL, HuggingFace ...) 🌈🐂  Replace OpenAI GPT with any LLMs in your app with one line.", "popularity": {"value": 756, "label": "stars"}, "url": "https://github.com/theodo-group/GenossGPT", "tags": ["inference"]}
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{"id": "hf-dataset:adams-story/datacomp200m", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "adams-story/datacomp200m", "date": "2023-07-19", "createdAt": "2023-07-12", "sourceUpdatedAt": "2023-07-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 106772 downloads.", "popularity": {"value": 106772, "label": "downloads"}, "url": "https://huggingface.co/datasets/adams-story/datacomp200m", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:image", "modality:tabular"]}
{"id": "github:epsilla-cloud/vectordb", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "epsilla-cloud/vectordb", "date": "2025-11-29", "createdAt": "2023-07-09", "sourceUpdatedAt": "2025-11-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Epsilla is a high performance Vector Database Management System", "popularity": {"value": 874, "label": "stars"}, "url": "https://github.com/epsilla-cloud/vectordb", "tags": ["vector-database", "vector-db"]}
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{"id": "hf-model:Xenova/multilingual-e5-small", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Xenova/multilingual-e5-small", "date": "2023-07-01", "createdAt": "2023-07-01", "sourceUpdatedAt": "2023-07-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1782632 downloads and tags: transformers.js, onnx, bert, feature-extraction.", "popularity": {"value": 1782632, "label": "downloads"}, "url": "https://huggingface.co/Xenova/multilingual-e5-small", "tags": ["base_model:intfloat/multilingual-e5-small", "base_model:quantized:intfloat/multilingual-e5-small", "bert", "embeddings", "feature-extraction", "onnx", "region:us", "transformers.js"]}
{"id": "github:agentera/agently", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AgentEra/Agently", "date": "2026-06-02", "createdAt": "2023-06-30", "sourceUpdatedAt": "2026-06-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[GenAI Application Development Framework]  🚀 Build GenAI application quick and easy 💬 Easy to interact with GenAI agent in code using structure data and chained-calls syntax 🧩 Use Event-Driven Flow *TriggerFlow* to manage complex GenAI working logic 🔀 Switc...", "popularity": {"value": 1581, "label": "stars"}, "url": "https://github.com/AgentEra/Agently", "tags": ["agents", "llmops"]}
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{"id": "hf-model:intfloat/multilingual-e5-small", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "intfloat/multilingual-e5-small", "date": "2023-06-30", "createdAt": "2023-06-30", "sourceUpdatedAt": "2023-06-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 8835604 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 8835604, "label": "downloads"}, "url": "https://huggingface.co/intfloat/multilingual-e5-small", "tags": ["bert", "mteb", "onnx", "openvino", "pytorch", "safetensors", "sentence transformers", "sentence-transformers"]}
{"id": "hf-model:intfloat/multilingual-e5-large", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "intfloat/multilingual-e5-large", "date": "2023-06-30", "createdAt": "2023-06-30", "sourceUpdatedAt": "2023-06-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 7380750 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 7380750, "label": "downloads"}, "url": "https://huggingface.co/intfloat/multilingual-e5-large", "tags": ["mteb", "onnx", "openvino", "pytorch", "safetensors", "sentence transformers", "sentence-transformers", "small-local"]}
{"id": "github:llm-tools/embedjs", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "llm-tools/embedJs", "date": "2025-11-17", "createdAt": "2023-06-29", "sourceUpdatedAt": "2025-11-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A NodeJS RAG framework to easily work with LLMs and embeddings", "popularity": {"value": 603, "label": "stars"}, "url": "https://github.com/llm-tools/embedJs", "tags": ["rag", "vector-database"]}
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{"id": "hf-model:colbert-ir/colbertv2.0", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "colbert-ir/colbertv2.0", "date": "2023-06-27", "createdAt": "2023-06-27", "sourceUpdatedAt": "2023-06-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 18700194 downloads and tags: transformers, pytorch, onnx, safetensors.", "popularity": {"value": 18700194, "label": "downloads"}, "url": "https://huggingface.co/colbert-ir/colbertv2.0", "tags": ["arxiv:2004.12832", "bert", "colbert", "en", "onnx", "pytorch", "safetensors", "small-local"]}
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{"id": "hf-dataset:mlfoundations/datacomp_pools", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mlfoundations/datacomp_pools", "date": "2023-08-21", "createdAt": "2023-02-01", "sourceUpdatedAt": "2023-08-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 72751 downloads.", "popularity": {"value": 72751, "label": "downloads"}, "url": "https://huggingface.co/datasets/mlfoundations/datacomp_pools", "tags": ["datasets", "license:cc-by-4.0", "modality:image", "region:us"]}
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{"id": "hf-dataset:huggingface/brand-assets", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "huggingface/brand-assets", "date": "2026-03-11", "createdAt": "2023-01-27", "sourceUpdatedAt": "2026-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 119098 downloads.", "popularity": {"value": 119098, "label": "downloads"}, "url": "https://huggingface.co/datasets/huggingface/brand-assets", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "modality:image", "region:us", "size_categories:n<1k"]}
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{"id": "hf-dataset:atokforps/latent_v1_fullrun_alpha3_04", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "atokforps/latent_v1_fullrun_alpha3_04", "date": "2023-02-02", "createdAt": "2023-01-21", "sourceUpdatedAt": "2023-02-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55918 downloads.", "popularity": {"value": 55918, "label": "downloads"}, "url": "https://huggingface.co/datasets/atokforps/latent_v1_fullrun_alpha3_04", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:atokforps/latent_v1_fullrun_alpha3_06", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "atokforps/latent_v1_fullrun_alpha3_06", "date": "2023-02-02", "createdAt": "2023-01-21", "sourceUpdatedAt": "2023-02-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50396 downloads.", "popularity": {"value": 50396, "label": "downloads"}, "url": "https://huggingface.co/datasets/atokforps/latent_v1_fullrun_alpha3_06", "tags": ["datasets", "region:us"]}
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{"id": "hf-dataset:EleutherAI/lambada_openai", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "EleutherAI/lambada_openai", "date": "2025-07-10", "createdAt": "2022-12-16", "sourceUpdatedAt": "2025-07-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 92798 downloads.", "popularity": {"value": 92798, "label": "downloads"}, "url": "https://huggingface.co/datasets/EleutherAI/lambada_openai", "tags": ["datasets", "format:parquet", "language:de", "language:en", "language:es", "language:fr", "language:it", "language_creators:machine-generated"]}
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{"id": "hf-model:Salesforce/blip-image-captioning-large", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Salesforce/blip-image-captioning-large", "date": "2022-12-13", "createdAt": "2022-12-13", "sourceUpdatedAt": "2022-12-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 755239 downloads and tags: transformers, pytorch, tf, safetensors.", "popularity": {"value": 755239, "label": "downloads"}, "url": "https://huggingface.co/Salesforce/blip-image-captioning-large", "tags": ["blip", "image-captioning", "image-text-to-text", "image-to-text", "multimodal", "pytorch", "safetensors", "tf"]}
{"id": "hf-dataset:allenai/objaverse", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/objaverse", "date": "2023-03-31", "createdAt": "2022-12-12", "sourceUpdatedAt": "2023-03-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 277275 downloads.", "popularity": {"value": 277275, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/objaverse", "tags": ["arxiv:2212.08051", "datasets", "language:en", "license:odc-by", "region:us"]}
{"id": "hf-model:Salesforce/blip-image-captioning-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "Salesforce/blip-image-captioning-base", "date": "2022-12-12", "createdAt": "2022-12-12", "sourceUpdatedAt": "2022-12-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2469092 downloads and tags: transformers, pytorch, tf, blip.", "popularity": {"value": 2469092, "label": "downloads"}, "url": "https://huggingface.co/Salesforce/blip-image-captioning-base", "tags": ["arxiv:2201.12086", "blip", "image-captioning", "image-text-to-text", "image-to-text", "multimodal", "pytorch", "tf"]}
{"id": "github:astrbotdevs/astrbot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "AstrBotDevs/AstrBot", "date": "2026-06-04", "createdAt": "2022-12-08", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨", "popularity": {"value": 33754, "label": "stars"}, "url": "https://github.com/AstrBotDevs/AstrBot", "tags": ["agents", "llm"]}
{"id": "github:langbot-app/langbot", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "langbot-app/LangBot", "date": "2026-06-03", "createdAt": "2022-12-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Production-grade platform for building agentic IM bots - 生产级多平台智能机器人开发平台. 提供 Agent、知识库编排、插件系统 / Bots for Discord / Slack / LINE / Telegram / WeChat(企业微信, 企微智能机器人, 公众号) / 飞书 / 钉钉 / QQ / Satori e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow,...", "popularity": {"value": 16199, "label": "stars"}, "url": "https://github.com/langbot-app/LangBot", "tags": ["rag", "ui-demo"]}
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{"id": "hf-dataset:shi-labs/oneformer_demo", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "shi-labs/oneformer_demo", "date": "2022-12-07", "createdAt": "2022-12-01", "sourceUpdatedAt": "2022-12-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 150061 downloads.", "popularity": {"value": 150061, "label": "downloads"}, "url": "https://huggingface.co/datasets/shi-labs/oneformer_demo", "tags": ["datasets", "region:us"]}
{"id": "github:pykeio/ort", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "pykeio/ort", "date": "2026-05-30", "createdAt": "2022-11-26", "sourceUpdatedAt": "2026-05-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Fast ML inference & training for ONNX models in Rust", "popularity": {"value": 2306, "label": "stars"}, "url": "https://github.com/pykeio/ort", "tags": ["inference"]}
{"id": "hf-dataset:huggingface-deep-rl-course/course-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "huggingface-deep-rl-course/course-images", "date": "2024-06-10", "createdAt": "2022-11-24", "sourceUpdatedAt": "2024-06-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 73154 downloads.", "popularity": {"value": 73154, "label": "downloads"}, "url": "https://huggingface.co/datasets/huggingface-deep-rl-course/course-images", "tags": ["datasets", "region:us"]}
{"id": "hf-dataset:sayakpaul/nyu_depth_v2", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "sayakpaul/nyu_depth_v2", "date": "2022-12-12", "createdAt": "2022-11-22", "sourceUpdatedAt": "2022-12-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 51659 downloads.", "popularity": {"value": 51659, "label": "downloads"}, "url": "https://huggingface.co/datasets/sayakpaul/nyu_depth_v2", "tags": ["arxiv:1903.03273", "datasets", "depth-estimation", "language:en", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:image"]}
{"id": "github:zjhellofss/kuiperinfer", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zjhellofss/KuiperInfer", "date": "2025-06-22", "createdAt": "2022-11-21", "sourceUpdatedAt": "2025-06-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step", "popularity": {"value": 3434, "label": "stars"}, "url": "https://github.com/zjhellofss/KuiperInfer", "tags": ["inference"]}
{"id": "github:currenjin/site-for-developers", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "currenjin/site-for-developers", "date": "2026-03-26", "createdAt": "2022-11-19", "sourceUpdatedAt": "2026-03-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🌎💎 개발자들의 첫 번째 북마크", "popularity": {"value": 1168, "label": "stars"}, "url": "https://github.com/currenjin/site-for-developers", "tags": ["ai-tools", "developer-tools"]}
{"id": "hf-dataset:joelniklaus/MultiLegalPile_Wikipedia_Filtered", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "joelniklaus/MultiLegalPile_Wikipedia_Filtered", "date": "2022-11-29", "createdAt": "2022-11-17", "sourceUpdatedAt": "2022-11-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 71054 downloads.", "popularity": {"value": 71054, "label": "downloads"}, "url": "https://huggingface.co/datasets/joelniklaus/MultiLegalPile_Wikipedia_Filtered", "tags": ["annotations_creators:other", "datasets", "language:bg", "language:cs", "language:da", "language:de", "language:el", "language:en"]}
{"id": "hf-dataset:WINGNUS/ACL-OCL", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "WINGNUS/ACL-OCL", "date": "2023-09-21", "createdAt": "2022-11-15", "sourceUpdatedAt": "2023-09-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 606197 downloads.", "popularity": {"value": 606197, "label": "downloads"}, "url": "https://huggingface.co/datasets/WINGNUS/ACL-OCL", "tags": ["acl", "datasets", "language:en", "language_creators:found", "license:mit", "multilinguality:monolingual", "region:us", "research papers"]}
{"id": "github:arize-ai/phoenix", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Arize-ai/phoenix", "date": "2026-06-04", "createdAt": "2022-11-09", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI Observability & Evaluation", "popularity": {"value": 9972, "label": "stars"}, "url": "https://github.com/Arize-ai/phoenix", "tags": ["evaluation", "llmops"]}
{"id": "hf-dataset:hf-doc-build/doc-build-dev", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-doc-build/doc-build-dev", "date": "2026-04-20", "createdAt": "2022-11-08", "sourceUpdatedAt": "2026-04-20", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 414759 downloads.", "popularity": {"value": 414759, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-doc-build/doc-build-dev", "tags": ["datasets", "documentation", "license:mit", "region:us"]}
{"id": "github:triton-inference-server/pytriton", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "triton-inference-server/pytriton", "date": "2025-08-13", "createdAt": "2022-11-08", "sourceUpdatedAt": "2025-08-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "PyTriton is a Flask/FastAPI-like interface that simplifies Triton's deployment in Python environments.", "popularity": {"value": 843, "label": "stars"}, "url": "https://github.com/triton-inference-server/pytriton", "tags": ["inference"]}
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{"id": "github:run-llama/llama_index", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "run-llama/llama_index", "date": "2026-06-04", "createdAt": "2022-11-02", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "LlamaIndex is the leading document agent and OCR platform", "popularity": {"value": 49889, "label": "stars"}, "url": "https://github.com/run-llama/llama_index", "tags": ["agents", "application", "data", "fine-tuning", "framework", "llamaindex"]}
{"id": "github:open-source-legal/cite", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Open-Source-Legal/cite", "date": "2026-06-04", "createdAt": "2022-10-24", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Ground truth layer for humans and AI agents working together. Version control for knowledge.", "popularity": {"value": 1343, "label": "stars"}, "url": "https://github.com/Open-Source-Legal/cite", "tags": ["agents", "vector-database"]}
{"id": "hf-dataset:hf-doc-build/doc-build", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-doc-build/doc-build", "date": "2026-06-03", "createdAt": "2022-10-24", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 192651 downloads.", "popularity": {"value": 192651, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-doc-build/doc-build", "tags": ["datasets", "license:mit", "region:us"]}
{"id": "github:steven2358/awesome-generative-ai", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "steven2358/awesome-generative-ai", "date": "2026-05-29", "createdAt": "2022-10-20", "sourceUpdatedAt": "2026-05-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A curated list of modern Generative Artificial Intelligence projects and services", "popularity": {"value": 12109, "label": "stars"}, "url": "https://github.com/steven2358/awesome-generative-ai", "tags": ["generative-ai", "tools"]}
{"id": "github:langchain-ai/langchain", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "langchain-ai/langchain", "date": "2026-06-04", "createdAt": "2022-10-17", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The agent engineering platform.", "popularity": {"value": 138448, "label": "stars"}, "url": "https://github.com/langchain-ai/langchain", "tags": ["agents", "ai", "ai-agents", "anthropic", "chatgpt", "deepagents"]}
{"id": "github:ai-forever/kandinsky-2", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ai-forever/Kandinsky-2", "date": "2024-05-01", "createdAt": "2022-10-14", "sourceUpdatedAt": "2024-05-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Kandinsky 2 — multilingual text2image latent diffusion model", "popularity": {"value": 2814, "label": "stars"}, "url": "https://github.com/ai-forever/Kandinsky-2", "tags": ["text-to-image", "tools"]}
{"id": "hf-dataset:bigscience/xP3", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bigscience/xP3", "date": "2023-05-30", "createdAt": "2022-10-10", "sourceUpdatedAt": "2023-05-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62441 downloads.", "popularity": {"value": 62441, "label": "downloads"}, "url": "https://huggingface.co/datasets/bigscience/xP3", "tags": ["annotations_creators:crowdsourced", "annotations_creators:expert-generated", "arxiv:2211.01786", "datasets", "language:ak", "language:ar", "language:as", "language:bm"]}
{"id": "github:huggingface/text-generation-inference", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "huggingface/text-generation-inference", "date": "2026-03-21", "createdAt": "2022-10-08", "sourceUpdatedAt": "2026-03-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Large Language Model Text Generation Inference", "popularity": {"value": 10859, "label": "stars"}, "url": "https://github.com/huggingface/text-generation-inference", "tags": ["bloom", "deep-learning", "falcon", "gpt", "inference", "nlp"]}
{"id": "github:chenwu98/cycle-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "ChenWu98/cycle-diffusion", "date": "2023-12-31", "createdAt": "2022-10-08", "sourceUpdatedAt": "2023-12-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "[ICCV 2023] A latent space for stochastic diffusion models", "popularity": {"value": 656, "label": "stars"}, "url": "https://github.com/ChenWu98/cycle-diffusion", "tags": ["text-to-image", "tools"]}
{"id": "github:chroma-core/chroma", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "chroma-core/chroma", "date": "2026-06-04", "createdAt": "2022-10-05", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Search infrastructure for AI", "popularity": {"value": 28198, "label": "stars"}, "url": "https://github.com/chroma-core/chroma", "tags": ["agents", "ai", "ai-agents", "database", "rust", "rust-lang", "vector-db"]}
{"id": "hf-dataset:nuprl/MultiPL-E", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nuprl/MultiPL-E", "date": "2025-07-15", "createdAt": "2022-09-28", "sourceUpdatedAt": "2025-07-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 57211 downloads.", "popularity": {"value": 57211, "label": "downloads"}, "url": "https://huggingface.co/datasets/nuprl/MultiPL-E", "tags": ["annotations_creators:machine-generated", "arxiv:2301.03988", "arxiv:2305.06161", "datasets", "doi:10.57967/hf/4446", "format:parquet", "language:en", "language_creators:expert-generated"]}
{"id": "hf-model:openai/whisper-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/whisper-base", "date": "2022-09-26", "createdAt": "2022-09-26", "sourceUpdatedAt": "2022-09-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3277932 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 3277932, "label": "downloads"}, "url": "https://huggingface.co/openai/whisper-base", "tags": ["audio", "automatic-speech-recognition", "jax", "pytorch", "safetensors", "tf", "transformers", "whisper"]}
{"id": "hf-model:openai/whisper-small", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/whisper-small", "date": "2022-09-26", "createdAt": "2022-09-26", "sourceUpdatedAt": "2022-09-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2482731 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 2482731, "label": "downloads"}, "url": "https://huggingface.co/openai/whisper-small", "tags": ["audio", "automatic-speech-recognition", "jax", "pytorch", "safetensors", "tf", "transformers", "whisper"]}
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{"id": "github:yangling0818/diffusion-models-papers-survey-taxonomy", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy", "date": "2025-09-27", "createdAt": "2022-09-12", "sourceUpdatedAt": "2025-09-27", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Diffusion model papers, survey, and taxonomy", "popularity": {"value": 3344, "label": "stars"}, "url": "https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy", "tags": ["text-to-image", "tools"]}
{"id": "github:xavierxiao/dreambooth-stable-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "XavierXiao/Dreambooth-Stable-Diffusion", "date": "2022-12-08", "createdAt": "2022-09-06", "sourceUpdatedAt": "2022-12-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion", "popularity": {"value": 7739, "label": "stars"}, "url": "https://github.com/XavierXiao/Dreambooth-Stable-Diffusion", "tags": ["text-to-image", "tools"]}
{"id": "github:superduper-io/superduper", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "superduper-io/superduper", "date": "2025-09-01", "createdAt": "2022-08-30", "sourceUpdatedAt": "2025-09-01", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Superduper: End-to-end framework for building custom AI applications and agents.", "popularity": {"value": 5287, "label": "stars"}, "url": "https://github.com/superduper-io/superduper", "tags": ["agents", "inference"]}
{"id": "hf-dataset:mschi/blogspot_raw", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mschi/blogspot_raw", "date": "2022-09-13", "createdAt": "2022-08-29", "sourceUpdatedAt": "2022-09-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 56087 downloads.", "popularity": {"value": 56087, "label": "downloads"}, "url": "https://huggingface.co/datasets/mschi/blogspot_raw", "tags": ["blogger", "blogspot", "datasets", "format:imagefolder", "language:en", "language_creators:other", "library:datasets", "library:mlcroissant"]}
{"id": "github:vicgalle/stable-diffusion-aesthetic-gradients", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "vicgalle/stable-diffusion-aesthetic-gradients", "date": "2022-10-21", "createdAt": "2022-08-25", "sourceUpdatedAt": "2022-10-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Personalization for Stable Diffusion via Aesthetic Gradients 🎨", "popularity": {"value": 743, "label": "stars"}, "url": "https://github.com/vicgalle/stable-diffusion-aesthetic-gradients", "tags": ["text-to-image", "tools"]}
{"id": "github:fboulnois/stable-diffusion-docker", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "fboulnois/stable-diffusion-docker", "date": "2023-12-29", "createdAt": "2022-08-23", "sourceUpdatedAt": "2023-12-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Run the official Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint.", "popularity": {"value": 748, "label": "stars"}, "url": "https://github.com/fboulnois/stable-diffusion-docker", "tags": ["text-to-image", "tools"]}
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{"id": "github:zhayujie/cowagent", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zhayujie/CowAgent", "date": "2026-06-03", "createdAt": "2022-08-07", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, autonomously grows with memory and knowledge. Multi-model, multi-channel. Lightweight, extensible, one-line install. (formerly chatgpt-on-wechat)", "popularity": {"value": 45046, "label": "stars"}, "url": "https://github.com/zhayujie/CowAgent", "tags": ["agents", "llm"]}
{"id": "hf-dataset:bigscience/evaluation-results", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bigscience/evaluation-results", "date": "2023-05-28", "createdAt": "2022-08-01", "sourceUpdatedAt": "2023-05-28", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face dataset with 50612 downloads.", "popularity": {"value": 50612, "label": "downloads"}, "url": "https://huggingface.co/datasets/bigscience/evaluation-results", "tags": ["datasets", "region:us", "size_categories:100m<n<1b", "task_categories:other"]}
{"id": "hf-dataset:AI-Growth-Lab/patents_claims_1.5m_traim_test", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "AI-Growth-Lab/patents_claims_1.5m_traim_test", "date": "2022-07-31", "createdAt": "2022-07-31", "sourceUpdatedAt": "2022-07-31", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55244 downloads.", "popularity": {"value": 55244, "label": "downloads"}, "url": "https://huggingface.co/datasets/AI-Growth-Lab/patents_claims_1.5m_traim_test", "tags": ["datasets", "format:csv", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:tabular", "modality:text"]}
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{"id": "hf-model:naver-clova-ix/donut-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "naver-clova-ix/donut-base", "date": "2022-07-19", "createdAt": "2022-07-19", "sourceUpdatedAt": "2022-07-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 148263 downloads and tags: transformers, pytorch, vision-encoder-decoder, image-text-to-text.", "popularity": {"value": 148263, "label": "downloads"}, "url": "https://huggingface.co/naver-clova-ix/donut-base", "tags": ["arxiv:2111.15664", "coding", "donut", "image-text-to-text", "image-to-text", "pytorch", "transformers", "vision"]}
{"id": "github:infiniflow/infinity", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "infiniflow/infinity", "date": "2026-05-24", "createdAt": "2022-07-18", "sourceUpdatedAt": "2026-05-24", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.", "popularity": {"value": 4547, "label": "stars"}, "url": "https://github.com/infiniflow/infinity", "tags": ["tools", "vector-database"]}
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{"id": "github:kuprel/min-dalle", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "kuprel/min-dalle", "date": "2025-04-28", "createdAt": "2022-06-27", "sourceUpdatedAt": "2025-04-28", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch", "popularity": {"value": 3495, "label": "stars"}, "url": "https://github.com/kuprel/min-dalle", "tags": ["text-to-image", "tools"]}
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{"id": "hf-dataset:julien-c/kaggle-hugomathien-soccer", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "julien-c/kaggle-hugomathien-soccer", "date": "2022-10-25", "createdAt": "2022-06-17", "sourceUpdatedAt": "2022-10-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 89199 downloads.", "popularity": {"value": 89199, "label": "downloads"}, "url": "https://huggingface.co/datasets/julien-c/kaggle-hugomathien-soccer", "tags": ["datasets", "license:odbl", "region:us"]}
{"id": "hf-dataset:truthfulqa/truthful_qa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "truthfulqa/truthful_qa", "date": "2024-01-04", "createdAt": "2022-06-08", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 98238 downloads.", "popularity": {"value": 98238, "label": "downloads"}, "url": "https://huggingface.co/datasets/truthfulqa/truthful_qa", "tags": ["annotations_creators:expert-generated", "arxiv:2109.07958", "datasets", "format:parquet", "language:en", "language_creators:expert-generated", "library:datasets", "library:mlcroissant"]}
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{"id": "hf-model:facebook/opt-125m", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "facebook/opt-125m", "date": "2022-05-11", "createdAt": "2022-05-11", "sourceUpdatedAt": "2022-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 11259224 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 11259224, "label": "downloads"}, "url": "https://huggingface.co/facebook/opt-125m", "tags": ["arxiv:2205.01068", "en", "jax", "llm", "opt", "pytorch", "text-generation", "tf"]}
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{"id": "github:kusionstack/kusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "KusionStack/kusion", "date": "2026-01-04", "createdAt": "2022-05-05", "sourceUpdatedAt": "2026-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Declarative Intent Driven Platform Orchestrator for Internal Developer Platform (IDP).", "popularity": {"value": 1311, "label": "stars"}, "url": "https://github.com/KusionStack/kusion", "tags": ["llmops", "tools"]}
{"id": "hf-dataset:ILSVRC/imagenet-1k", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ILSVRC/imagenet-1k", "date": "2025-09-17", "createdAt": "2022-05-02", "sourceUpdatedAt": "2025-09-17", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 78584 downloads.", "popularity": {"value": 78584, "label": "downloads"}, "url": "https://huggingface.co/datasets/ILSVRC/imagenet-1k", "tags": ["annotations_creators:crowdsourced", "arxiv:1409.0575", "arxiv:1811.12231", "arxiv:1912.07726", "arxiv:2109.13228", "datasets", "format:optimized-parquet", "format:parquet"]}
{"id": "github:zai-org/cogview2", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "zai-org/CogView2", "date": "2022-08-03", "createdAt": "2022-04-25", "sourceUpdatedAt": "2022-08-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "official code repo for paper \"CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers\"", "popularity": {"value": 955, "label": "stars"}, "url": "https://github.com/zai-org/CogView2", "tags": ["text-to-image", "tools"]}
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{"id": "hf-dataset:google/fleurs", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google/fleurs", "date": "2026-05-15", "createdAt": "2022-04-19", "sourceUpdatedAt": "2026-05-15", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63584 downloads.", "popularity": {"value": 63584, "label": "downloads"}, "url": "https://huggingface.co/datasets/google/fleurs", "tags": ["annotations_creators:crowdsourced", "annotations_creators:expert-generated", "annotations_creators:machine-generated", "arxiv:2106.03193", "arxiv:2205.12446", "datasets", "format:parquet", "language:afr"]}
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{"id": "github:lucidrains/dalle2-pytorch", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "lucidrains/DALLE2-pytorch", "date": "2024-05-11", "createdAt": "2022-04-07", "sourceUpdatedAt": "2024-05-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network,  in Pytorch", "popularity": {"value": 11312, "label": "stars"}, "url": "https://github.com/lucidrains/DALLE2-pytorch", "tags": ["text-to-image", "tools"]}
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{"id": "hf-dataset:oscar-corpus/OSCAR-2201", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "oscar-corpus/OSCAR-2201", "date": "2025-08-06", "createdAt": "2022-03-14", "sourceUpdatedAt": "2025-08-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 54335 downloads.", "popularity": {"value": 54335, "label": "downloads"}, "url": "https://huggingface.co/datasets/oscar-corpus/OSCAR-2201", "tags": ["annotations_creators:no-annotation", "arxiv:2010.14571", "arxiv:2103.12028", "arxiv:2201.06642", "datasets", "language:af", "language:als", "language:am"]}
{"id": "github:giskard-ai/giskard-oss", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "Giskard-AI/giskard-oss", "date": "2026-06-04", "createdAt": "2022-03-06", "sourceUpdatedAt": "2026-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "🐢 Open-Source Evaluation & Testing library for LLM Agents", "popularity": {"value": 5417, "label": "stars"}, "url": "https://github.com/Giskard-AI/giskard-oss", "tags": ["agents", "llmops"]}
{"id": "hf-dataset:huggingface/documentation-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "huggingface/documentation-images", "date": "2026-06-03", "createdAt": "2022-03-02", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 2121293 downloads.", "popularity": {"value": 2121293, "label": "downloads"}, "url": "https://huggingface.co/datasets/huggingface/documentation-images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:cc-by-nc-sa-4.0", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:Skylion007/openwebtext", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Skylion007/openwebtext", "date": "2025-12-26", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-12-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 70923 downloads.", "popularity": {"value": 70923, "label": "downloads"}, "url": "https://huggingface.co/datasets/Skylion007/openwebtext", "tags": ["annotations_creators:no-annotation", "datasets", "format:parquet", "language:en", "language_creators:found", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:NortheasternUniversity/big_patent", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "NortheasternUniversity/big_patent", "date": "2025-09-25", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-09-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63821 downloads.", "popularity": {"value": 63821, "label": "downloads"}, "url": "https://huggingface.co/datasets/NortheasternUniversity/big_patent", "tags": ["annotations_creators:no-annotation", "arxiv:1906.03741", "datasets", "format:parquet", "language:en", "language_creators:found", "library:dask", "library:datasets"]}
{"id": "hf-dataset:hotpotqa/hotpot_qa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hotpotqa/hotpot_qa", "date": "2025-08-11", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-08-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 89976 downloads.", "popularity": {"value": 89976, "label": "downloads"}, "url": "https://huggingface.co/datasets/hotpotqa/hotpot_qa", "tags": ["annotations_creators:crowdsourced", "arxiv:1809.09600", "datasets", "format:parquet", "language:en", "language_creators:found", "library:dask", "library:datasets"]}
{"id": "hf-dataset:openslr/librispeech_asr", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "openslr/librispeech_asr", "date": "2025-07-25", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-07-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 109418 downloads.", "popularity": {"value": 109418, "label": "downloads"}, "url": "https://huggingface.co/datasets/openslr/librispeech_asr", "tags": ["annotations_creators:expert-generated", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "language_creators:expert-generated", "library:dask", "library:datasets"]}
{"id": "hf-dataset:allenai/winogrande", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/winogrande", "date": "2025-07-11", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-07-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 230822 downloads.", "popularity": {"value": 230822, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/winogrande", "tags": ["datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text"]}
{"id": "hf-dataset:Rowan/hellaswag", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Rowan/hellaswag", "date": "2025-07-10", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-07-10", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 276135 downloads.", "popularity": {"value": 276135, "label": "downloads"}, "url": "https://huggingface.co/datasets/Rowan/hellaswag", "tags": ["arxiv:1905.07830", "datasets", "format:parquet", "language:en", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars"]}
{"id": "hf-dataset:huggingface-course/documentation-images", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "huggingface-course/documentation-images", "date": "2025-06-13", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-06-13", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 259692 downloads.", "popularity": {"value": 259692, "label": "downloads"}, "url": "https://huggingface.co/datasets/huggingface-course/documentation-images", "tags": ["datasets", "format:imagefolder", "library:datasets", "library:mlcroissant", "license:apache-2.0", "modality:image", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:aps/super_glue", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "aps/super_glue", "date": "2025-05-16", "createdAt": "2022-03-02", "sourceUpdatedAt": "2025-05-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 188306 downloads.", "popularity": {"value": 188306, "label": "downloads"}, "url": "https://huggingface.co/datasets/aps/super_glue", "tags": ["annotations_creators:expert-generated", "arxiv:1905.00537", "datasets", "format:parquet", "language:en", "language_creators:other", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:facebook/multilingual_librispeech", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "facebook/multilingual_librispeech", "date": "2024-08-12", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-08-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 49124 downloads.", "popularity": {"value": 49124, "label": "downloads"}, "url": "https://huggingface.co/datasets/facebook/multilingual_librispeech", "tags": ["annotations_creators:expert-generated", "arxiv:2012.03411", "datasets", "format:parquet", "language:de", "language:en", "language:es", "language:fr"]}
{"id": "hf-dataset:ylecun/mnist", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ylecun/mnist", "date": "2024-08-08", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-08-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 93374 downloads.", "popularity": {"value": 93374, "label": "downloads"}, "url": "https://huggingface.co/datasets/ylecun/mnist", "tags": ["annotations_creators:expert-generated", "datasets", "format:parquet", "language:en", "language_creators:found", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:hf-internal-testing/librispeech_asr_dummy", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "hf-internal-testing/librispeech_asr_dummy", "date": "2024-06-19", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-06-19", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 118468 downloads.", "popularity": {"value": 118468, "label": "downloads"}, "url": "https://huggingface.co/datasets/hf-internal-testing/librispeech_asr_dummy", "tags": ["datasets", "format:parquet", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:audio", "modality:text"]}
{"id": "hf-dataset:cornell-movie-review-data/rotten_tomatoes", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cornell-movie-review-data/rotten_tomatoes", "date": "2024-03-18", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81570 downloads.", "popularity": {"value": 81570, "label": "downloads"}, "url": "https://huggingface.co/datasets/cornell-movie-review-data/rotten_tomatoes", "tags": ["annotations_creators:crowdsourced", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:facebook/wiki_dpr", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "facebook/wiki_dpr", "date": "2024-03-12", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-12", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 62186 downloads.", "popularity": {"value": 62186, "label": "downloads"}, "url": "https://huggingface.co/datasets/facebook/wiki_dpr", "tags": ["annotations_creators:no-annotation", "arxiv:2004.04906", "datasets", "language:en", "language_creators:crowdsourced", "license:cc-by-nc-4.0", "multilinguality:multilingual", "region:us"]}
{"id": "hf-dataset:legacy-datasets/wikipedia", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "legacy-datasets/wikipedia", "date": "2024-03-11", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-11", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 107180 downloads.", "popularity": {"value": 107180, "label": "downloads"}, "url": "https://huggingface.co/datasets/legacy-datasets/wikipedia", "tags": ["annotations_creators:no-annotation", "datasets", "language:aa", "language:ab", "language:ace", "language:af", "language:ak", "language:als"]}
{"id": "hf-dataset:cais/mmlu", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cais/mmlu", "date": "2024-03-08", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-08", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 545890 downloads.", "popularity": {"value": 545890, "label": "downloads"}, "url": "https://huggingface.co/datasets/cais/mmlu", "tags": ["annotations_creators:no-annotation", "arxiv:2005.00700", "arxiv:2005.14165", "arxiv:2008.02275", "arxiv:2009.03300", "datasets", "format:parquet", "language:en"]}
{"id": "hf-dataset:fancyzhx/ag_news", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "fancyzhx/ag_news", "date": "2024-03-07", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-07", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 122649 downloads.", "popularity": {"value": 122649, "label": "downloads"}, "url": "https://huggingface.co/datasets/fancyzhx/ag_news", "tags": ["annotations_creators:found", "datasets", "format:parquet", "language:en", "language_creators:found", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:rajpurkar/squad", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "rajpurkar/squad", "date": "2024-03-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 157331 downloads.", "popularity": {"value": 157331, "label": "downloads"}, "url": "https://huggingface.co/datasets/rajpurkar/squad", "tags": ["annotations_creators:crowdsourced", "arxiv:1606.05250", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "language_creators:found", "library:datasets"]}
{"id": "hf-dataset:bigscience/P3", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "bigscience/P3", "date": "2024-03-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-03-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 89399 downloads.", "popularity": {"value": 89399, "label": "downloads"}, "url": "https://huggingface.co/datasets/bigscience/P3", "tags": ["annotations_creators:crowdsourced", "annotations_creators:expert-generated", "arxiv:2110.08207", "datasets", "format:parquet", "language:en", "library:dask", "library:datasets"]}
{"id": "hf-dataset:nyu-mll/glue", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "nyu-mll/glue", "date": "2024-01-30", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-30", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 487638 downloads.", "popularity": {"value": 487638, "label": "downloads"}, "url": "https://huggingface.co/datasets/nyu-mll/glue", "tags": ["annotations_creators:other", "arxiv:1804.07461", "coreference-nli", "datasets", "format:parquet", "language:en", "language_creators:other", "library:datasets"]}
{"id": "hf-dataset:google/boolq", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google/boolq", "date": "2024-01-22", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 48213 downloads.", "popularity": {"value": 48213, "label": "downloads"}, "url": "https://huggingface.co/datasets/google/boolq", "tags": ["annotations_creators:crowdsourced", "arxiv:1905.10044", "datasets", "format:parquet", "language:en", "language_creators:found", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:abisee/cnn_dailymail", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "abisee/cnn_dailymail", "date": "2024-01-18", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 215887 downloads.", "popularity": {"value": 215887, "label": "downloads"}, "url": "https://huggingface.co/datasets/abisee/cnn_dailymail", "tags": ["annotations_creators:no-annotation", "datasets", "format:parquet", "language:en", "language_creators:found", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:ybisk/piqa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ybisk/piqa", "date": "2024-01-18", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-18", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 64713 downloads.", "popularity": {"value": 64713, "label": "downloads"}, "url": "https://huggingface.co/datasets/ybisk/piqa", "tags": ["annotations_creators:crowdsourced", "arxiv:1808.05326", "arxiv:1904.09728", "arxiv:1907.10641", "arxiv:1911.11641", "datasets", "language:en", "language_creators:crowdsourced"]}
{"id": "hf-dataset:allenai/c4", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/c4", "date": "2024-01-09", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 795122 downloads.", "popularity": {"value": 795122, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/c4", "tags": ["annotations_creators:no-annotation", "arxiv:1910.10683", "datasets", "language:af", "language:am", "language:ar", "language:az", "language:be"]}
{"id": "hf-dataset:wikimedia/wikipedia", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "wikimedia/wikipedia", "date": "2024-01-09", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-09", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 247259 downloads.", "popularity": {"value": 247259, "label": "downloads"}, "url": "https://huggingface.co/datasets/wikimedia/wikipedia", "tags": ["datasets", "format:parquet", "language:ab", "language:ace", "language:ady", "language:af", "language:alt", "language:am"]}
{"id": "hf-dataset:mandarjoshi/trivia_qa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "mandarjoshi/trivia_qa", "date": "2024-01-05", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 83775 downloads.", "popularity": {"value": 83775, "label": "downloads"}, "url": "https://huggingface.co/datasets/mandarjoshi/trivia_qa", "tags": ["annotations_creators:crowdsourced", "arxiv:1705.03551", "datasets", "format:parquet", "language:en", "language_creators:machine-generated", "library:dask", "library:datasets"]}
{"id": "hf-dataset:Salesforce/wikitext", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Salesforce/wikitext", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 1352327 downloads.", "popularity": {"value": 1352327, "label": "downloads"}, "url": "https://huggingface.co/datasets/Salesforce/wikitext", "tags": ["annotations_creators:no-annotation", "arxiv:1609.07843", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "library:dask", "library:datasets"]}
{"id": "hf-dataset:openai/openai_humaneval", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "openai/openai_humaneval", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 288341 downloads.", "popularity": {"value": 288341, "label": "downloads"}, "url": "https://huggingface.co/datasets/openai/openai_humaneval", "tags": ["annotations_creators:expert-generated", "arxiv:2107.03374", "code-generation", "datasets", "format:parquet", "language:en", "language_creators:expert-generated", "library:datasets"]}
{"id": "hf-dataset:stanfordnlp/imdb", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "stanfordnlp/imdb", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 275610 downloads.", "popularity": {"value": 275610, "label": "downloads"}, "url": "https://huggingface.co/datasets/stanfordnlp/imdb", "tags": ["annotations_creators:expert-generated", "datasets", "format:parquet", "language:en", "language_creators:expert-generated", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:google-research-datasets/mbpp", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google-research-datasets/mbpp", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 200528 downloads.", "popularity": {"value": 200528, "label": "downloads"}, "url": "https://huggingface.co/datasets/google-research-datasets/mbpp", "tags": ["annotations_creators:crowdsourced", "annotations_creators:expert-generated", "arxiv:2108.07732", "code-generation", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced"]}
{"id": "hf-dataset:allenai/openbookqa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/openbookqa", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 154150 downloads.", "popularity": {"value": 154150, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/openbookqa", "tags": ["annotations_creators:crowdsourced", "annotations_creators:expert-generated", "datasets", "format:parquet", "language:en", "language_creators:expert-generated", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:uoft-cs/cifar10", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "uoft-cs/cifar10", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 116340 downloads.", "popularity": {"value": 116340, "label": "downloads"}, "url": "https://huggingface.co/datasets/uoft-cs/cifar10", "tags": ["annotations_creators:crowdsourced", "datasets", "format:parquet", "language:en", "language_creators:found", "library:datasets", "library:mlcroissant", "library:pandas"]}
{"id": "hf-dataset:allenai/sciq", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/sciq", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 90848 downloads.", "popularity": {"value": 90848, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/sciq", "tags": ["annotations_creators:no-annotation", "arxiv:1707.06209", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:google-research-datasets/paws", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "google-research-datasets/paws", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 81081 downloads.", "popularity": {"value": 81081, "label": "downloads"}, "url": "https://huggingface.co/datasets/google-research-datasets/paws", "tags": ["annotations_creators:expert-generated", "annotations_creators:machine-generated", "arxiv:1904.01130", "datasets", "format:parquet", "language:en", "language_creators:machine-generated", "library:datasets"]}
{"id": "hf-dataset:cimec/lambada", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "cimec/lambada", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 55009 downloads.", "popularity": {"value": 55009, "label": "downloads"}, "url": "https://huggingface.co/datasets/cimec/lambada", "tags": ["annotations_creators:expert-generated", "datasets", "format:parquet", "language:en", "language_creators:found", "library:dask", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:tau/commonsense_qa", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "tau/commonsense_qa", "date": "2024-01-04", "createdAt": "2022-03-02", "sourceUpdatedAt": "2024-01-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 52870 downloads.", "popularity": {"value": 52870, "label": "downloads"}, "url": "https://huggingface.co/datasets/tau/commonsense_qa", "tags": ["annotations_creators:crowdsourced", "arxiv:1811.00937", "datasets", "format:parquet", "language:en", "language_creators:crowdsourced", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:allenai/ai2_arc", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "allenai/ai2_arc", "date": "2023-12-21", "createdAt": "2022-03-02", "sourceUpdatedAt": "2023-12-21", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 481704 downloads.", "popularity": {"value": 481704, "label": "downloads"}, "url": "https://huggingface.co/datasets/allenai/ai2_arc", "tags": ["annotations_creators:found", "arxiv:1803.05457", "datasets", "format:parquet", "language:en", "language_creators:found", "library:datasets", "library:mlcroissant"]}
{"id": "hf-dataset:lhoestq/custom_squad", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "lhoestq/custom_squad", "date": "2022-10-25", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-10-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 69800 downloads.", "popularity": {"value": 69800, "label": "downloads"}, "url": "https://huggingface.co/datasets/lhoestq/custom_squad", "tags": ["annotations_creators:crowdsourced", "arxiv:1606.05250", "datasets", "language:en", "language_creators:crowdsourced", "language_creators:found", "license:cc-by-4.0", "multilinguality:monolingual"]}
{"id": "hf-model:sentence-transformers/all-MiniLM-L6-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/all-MiniLM-L6-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 257461566 downloads and tags: sentence-transformers, pytorch, tf, rust.", "popularity": {"value": 257461566, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2", "tags": ["bert", "onnx", "openvino", "pytorch", "rust", "safetensors", "sentence-transformers", "small-local"]}
{"id": "hf-model:cross-encoder/ms-marco-MiniLM-L6-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "cross-encoder/ms-marco-MiniLM-L6-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 71259114 downloads and tags: sentence-transformers, pytorch, jax, onnx.", "popularity": {"value": 71259114, "label": "downloads"}, "url": "https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2", "tags": ["bert", "jax", "onnx", "openvino", "pytorch", "rerankers", "safetensors", "sentence-transformers"]}
{"id": "hf-model:google-bert/bert-base-uncased", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "google-bert/bert-base-uncased", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 67684020 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 67684020, "label": "downloads"}, "url": "https://huggingface.co/google-bert/bert-base-uncased", "tags": ["coreml", "jax", "onnx", "pytorch", "rust", "safetensors", "small-local", "tf"]}
{"id": "hf-model:google/electra-base-discriminator", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "google/electra-base-discriminator", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 58018394 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 58018394, "label": "downloads"}, "url": "https://huggingface.co/google/electra-base-discriminator", "tags": ["electra", "en", "jax", "llm", "pretraining", "pytorch", "rust", "tf"]}
{"id": "hf-model:sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 50271673 downloads and tags: sentence-transformers, pytorch, tf, onnx.", "popularity": {"value": 50271673, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "openvino", "pytorch", "safetensors", "sentence-transformers"]}
{"id": "hf-model:sentence-transformers/all-mpnet-base-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/all-mpnet-base-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 35748401 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 35748401, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/all-mpnet-base-v2", "tags": ["embeddings", "feature-extraction", "fill-mask", "mpnet", "onnx", "openvino", "pytorch", "safetensors"]}
{"id": "hf-model:openai/clip-vit-large-patch14", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/clip-vit-large-patch14", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 24305504 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 24305504, "label": "downloads"}, "url": "https://huggingface.co/openai/clip-vit-large-patch14", "tags": ["clip", "jax", "llm", "pytorch", "safetensors", "tf", "transformers", "vision"]}
{"id": "hf-model:openai/clip-vit-base-patch32", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai/clip-vit-base-patch32", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 22714341 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 22714341, "label": "downloads"}, "url": "https://huggingface.co/openai/clip-vit-base-patch32", "tags": ["arxiv:2103.00020", "clip", "jax", "llm", "pytorch", "tf", "transformers", "vision"]}
{"id": "hf-model:FacebookAI/xlm-roberta-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "FacebookAI/xlm-roberta-base", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 22579471 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 22579471, "label": "downloads"}, "url": "https://huggingface.co/FacebookAI/xlm-roberta-base", "tags": ["fill-mask", "jax", "onnx", "pytorch", "safetensors", "small-local", "tf", "transformers"]}
{"id": "hf-model:FacebookAI/roberta-large", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "FacebookAI/roberta-large", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 16788681 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 16788681, "label": "downloads"}, "url": "https://huggingface.co/FacebookAI/roberta-large", "tags": ["fill-mask", "jax", "onnx", "pytorch", "roberta", "safetensors", "small-local", "tf"]}
{"id": "hf-model:openai-community/gpt2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "openai-community/gpt2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 16035108 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 16035108, "label": "downloads"}, "url": "https://huggingface.co/openai-community/gpt2", "tags": ["jax", "onnx", "pytorch", "rust", "safetensors", "small-local", "tf", "tflite"]}
{"id": "hf-model:FacebookAI/roberta-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "FacebookAI/roberta-base", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 15438624 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 15438624, "label": "downloads"}, "url": "https://huggingface.co/FacebookAI/roberta-base", "tags": ["fill-mask", "jax", "llm", "pytorch", "roberta", "rust", "safetensors", "tf"]}
{"id": "hf-model:distilbert/distilbert-base-uncased", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "distilbert/distilbert-base-uncased", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 12478135 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 12478135, "label": "downloads"}, "url": "https://huggingface.co/distilbert/distilbert-base-uncased", "tags": ["distilbert", "fill-mask", "jax", "llm", "pytorch", "rust", "safetensors", "tf"]}
{"id": "hf-model:sentence-transformers/paraphrase-multilingual-mpnet-base-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/paraphrase-multilingual-mpnet-base-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 7653848 downloads and tags: sentence-transformers, pytorch, tf, onnx.", "popularity": {"value": 7653848, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2", "tags": ["embeddings", "feature-extraction", "onnx", "openvino", "pytorch", "safetensors", "sentence-transformers", "tf"]}
{"id": "hf-model:sentence-transformers/all-MiniLM-L12-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/all-MiniLM-L12-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 5763181 downloads and tags: sentence-transformers, pytorch, rust, onnx.", "popularity": {"value": 5763181, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "openvino", "pytorch", "rust", "safetensors"]}
{"id": "hf-model:distilbert/distilgpt2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "distilbert/distilgpt2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4518996 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 4518996, "label": "downloads"}, "url": "https://huggingface.co/distilbert/distilgpt2", "tags": ["coreml", "jax", "llm", "pytorch", "rust", "safetensors", "tf", "tflite"]}
{"id": "hf-model:sentence-transformers/paraphrase-MiniLM-L6-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/paraphrase-MiniLM-L6-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 4414845 downloads and tags: sentence-transformers, pytorch, tf, onnx.", "popularity": {"value": 4414845, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L6-v2", "tags": ["bert", "embeddings", "feature-extraction", "onnx", "openvino", "pytorch", "safetensors", "sentence-transformers"]}
{"id": "hf-model:jonatasgrosman/wav2vec2-large-xlsr-53-russian", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jonatasgrosman/wav2vec2-large-xlsr-53-russian", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3599166 downloads and tags: transformers, pytorch, jax, wav2vec2.", "popularity": {"value": 3599166, "label": "downloads"}, "url": "https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-russian", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "jax", "mozilla-foundation/common_voice_6_0", "pytorch", "transformers", "wav2vec2"]}
{"id": "hf-model:sentence-transformers/multi-qa-mpnet-base-dot-v1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/multi-qa-mpnet-base-dot-v1", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3172066 downloads and tags: sentence-transformers, pytorch, onnx, safetensors.", "popularity": {"value": 3172066, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1", "tags": ["embeddings", "feature-extraction", "fill-mask", "mpnet", "onnx", "openvino", "pytorch", "safetensors"]}
{"id": "hf-model:jonatasgrosman/wav2vec2-large-xlsr-53-portuguese", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jonatasgrosman/wav2vec2-large-xlsr-53-portuguese", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 3057860 downloads and tags: transformers, pytorch, jax, wav2vec2.", "popularity": {"value": 3057860, "label": "downloads"}, "url": "https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "jax", "mozilla-foundation/common_voice_6_0", "pytorch", "transformers", "wav2vec2"]}
{"id": "hf-model:pyannote/voice-activity-detection", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "pyannote/voice-activity-detection", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2993942 downloads and tags: pyannote-audio, pyannote, pyannote-audio-pipeline, audio.", "popularity": {"value": 2993942, "label": "downloads"}, "url": "https://huggingface.co/pyannote/voice-activity-detection", "tags": ["audio", "pyannote", "pyannote-audio", "pyannote-audio-pipeline", "speaker", "speech", "voice", "voice-activity-detection"]}
{"id": "hf-model:sentence-transformers/all-distilroberta-v1", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/all-distilroberta-v1", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 2472080 downloads and tags: sentence-transformers, pytorch, rust, onnx.", "popularity": {"value": 2472080, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/all-distilroberta-v1", "tags": ["fill-mask", "onnx", "openvino", "pytorch", "roberta", "rust", "safetensors", "sentence-transformers"]}
{"id": "hf-model:cambridgeltl/SapBERT-from-PubMedBERT-fulltext", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "cambridgeltl/SapBERT-from-PubMedBERT-fulltext", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1761277 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 1761277, "label": "downloads"}, "url": "https://huggingface.co/cambridgeltl/SapBERT-from-PubMedBERT-fulltext", "tags": ["bert", "biomedical", "embeddings", "feature-extraction", "jax", "pytorch", "safetensors", "tf"]}
{"id": "hf-model:sentence-transformers/paraphrase-mpnet-base-v2", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "sentence-transformers/paraphrase-mpnet-base-v2", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1609697 downloads and tags: sentence-transformers, pytorch, tf, onnx.", "popularity": {"value": 1609697, "label": "downloads"}, "url": "https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2", "tags": ["embeddings", "feature-extraction", "mpnet", "onnx", "openvino", "pytorch", "safetensors", "sentence-transformers"]}
{"id": "hf-model:jonatasgrosman/wav2vec2-large-xlsr-53-polish", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jonatasgrosman/wav2vec2-large-xlsr-53-polish", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1567406 downloads and tags: transformers, pytorch, jax, wav2vec2.", "popularity": {"value": 1567406, "label": "downloads"}, "url": "https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-polish", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "jax", "mozilla-foundation/common_voice_6_0", "pytorch", "transformers", "wav2vec2"]}
{"id": "hf-model:jonatasgrosman/wav2vec2-large-xlsr-53-japanese", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "jonatasgrosman/wav2vec2-large-xlsr-53-japanese", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1480282 downloads and tags: transformers, pytorch, jax, wav2vec2.", "popularity": {"value": 1480282, "label": "downloads"}, "url": "https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-japanese", "tags": ["audio", "automatic-speech-recognition", "jax", "pytorch", "speech", "transformers", "wav2vec2", "xlsr-fine-tuning-week"]}
{"id": "hf-model:YituTech/conv-bert-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "YituTech/conv-bert-base", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 1150727 downloads and tags: transformers, pytorch, tf, convbert.", "popularity": {"value": 1150727, "label": "downloads"}, "url": "https://huggingface.co/YituTech/conv-bert-base", "tags": ["convbert", "deploy:azure", "embeddings", "endpoints_compatible", "feature-extraction", "pytorch", "region:us", "tf"]}
{"id": "hf-model:microsoft/wavlm-base-plus", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/wavlm-base-plus", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 786595 downloads and tags: transformers, pytorch, wavlm, feature-extraction.", "popularity": {"value": 786595, "label": "downloads"}, "url": "https://huggingface.co/microsoft/wavlm-base-plus", "tags": ["arxiv:1912.07875", "arxiv:2106.06909", "embeddings", "en", "feature-extraction", "pytorch", "speech", "transformers"]}
{"id": "hf-model:microsoft/wavlm-large", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/wavlm-large", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 734970 downloads and tags: transformers, pytorch, wavlm, feature-extraction.", "popularity": {"value": 734970, "label": "downloads"}, "url": "https://huggingface.co/microsoft/wavlm-large", "tags": ["arxiv:1912.07875", "arxiv:2106.06909", "embeddings", "en", "feature-extraction", "pytorch", "speech", "transformers"]}
{"id": "hf-model:facebook/bart-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "facebook/bart-base", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-03T05:03:47+00:00", "summary": "Hugging Face model with 707664 downloads and tags: transformers, pytorch, tf, jax.", "popularity": {"value": 707664, "label": "downloads"}, "url": "https://huggingface.co/facebook/bart-base", "tags": ["bart", "embeddings", "en", "feature-extraction", "jax", "pytorch", "safetensors", "tf"]}
{"id": "hf-model:microsoft/trocr-base-printed", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/trocr-base-printed", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 384552 downloads and tags: transformers, pytorch, safetensors, vision-encoder-decoder.", "popularity": {"value": 384552, "label": "downloads"}, "url": "https://huggingface.co/microsoft/trocr-base-printed", "tags": ["arxiv:2109.10282", "coding", "image-text-to-text", "image-to-text", "pytorch", "safetensors", "transformers", "trocr"]}
{"id": "hf-model:kha-white/manga-ocr-base", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "kha-white/manga-ocr-base", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 381121 downloads and tags: transformers, pytorch, image-to-text, ja.", "popularity": {"value": 381121, "label": "downloads"}, "url": "https://huggingface.co/kha-white/manga-ocr-base", "tags": ["dataset:manga109s", "endpoints_compatible", "image-to-text", "ja", "license:apache-2.0", "multimodal", "pytorch", "region:us"]}
{"id": "hf-model:microsoft/trocr-large-handwritten", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/trocr-large-handwritten", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 260215 downloads and tags: transformers, pytorch, vision-encoder-decoder, image-text-to-text.", "popularity": {"value": 260215, "label": "downloads"}, "url": "https://huggingface.co/microsoft/trocr-large-handwritten", "tags": ["arxiv:2109.10282", "coding", "endpoints_compatible", "image-text-to-text", "image-to-text", "pytorch", "transformers", "trocr"]}
{"id": "hf-model:microsoft/trocr-small-handwritten", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/trocr-small-handwritten", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 166237 downloads and tags: transformers, pytorch, vision-encoder-decoder, image-text-to-text.", "popularity": {"value": 166237, "label": "downloads"}, "url": "https://huggingface.co/microsoft/trocr-small-handwritten", "tags": ["arxiv:2109.10282", "coding", "endpoints_compatible", "image-text-to-text", "image-to-text", "pytorch", "transformers", "trocr"]}
{"id": "hf-model:nlpconnect/vit-gpt2-image-captioning", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "nlpconnect/vit-gpt2-image-captioning", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 158505 downloads and tags: transformers, pytorch, vision-encoder-decoder, image-text-to-text.", "popularity": {"value": 158505, "label": "downloads"}, "url": "https://huggingface.co/nlpconnect/vit-gpt2-image-captioning", "tags": ["coding", "doi:10.57967/hf/0222", "image-captioning", "image-text-to-text", "image-to-text", "license:apache-2.0", "pytorch", "transformers"]}
{"id": "hf-model:microsoft/trocr-base-handwritten", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/trocr-base-handwritten", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 157889 downloads and tags: transformers, pytorch, safetensors, vision-encoder-decoder.", "popularity": {"value": 157889, "label": "downloads"}, "url": "https://huggingface.co/microsoft/trocr-base-handwritten", "tags": ["arxiv:2109.10282", "coding", "image-text-to-text", "image-to-text", "pytorch", "safetensors", "transformers", "trocr"]}
{"id": "hf-model:microsoft/trocr-large-printed", "source": "Hugging Face Models", "sourceId": "huggingface-models", "kind": "model", "name": "microsoft/trocr-large-printed", "date": "2022-03-02", "createdAt": "2022-03-02", "sourceUpdatedAt": "2022-03-02", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face model with 134888 downloads and tags: transformers, pytorch, safetensors, vision-encoder-decoder.", "popularity": {"value": 134888, "label": "downloads"}, "url": "https://huggingface.co/microsoft/trocr-large-printed", "tags": ["arxiv:2109.10282", "coding", "image-text-to-text", "image-to-text", "pytorch", "safetensors", "transformers", "trocr"]}
{"id": "hf-dataset:merve/coco", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "merve/coco", "date": "2021-11-22", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-11-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 63602 downloads.", "popularity": {"value": 63602, "label": "downloads"}, "url": "https://huggingface.co/datasets/merve/coco", "tags": ["datasets", "modality:image", "region:us"]}
{"id": "hf-dataset:dalle-mini/wit", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "dalle-mini/wit", "date": "2021-09-14", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-09-14", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 50270 downloads.", "popularity": {"value": 50270, "label": "downloads"}, "url": "https://huggingface.co/datasets/dalle-mini/wit", "tags": ["datasets", "format:parquet", "library:dask", "library:datasets", "library:mlcroissant", "library:polars", "modality:image", "modality:tabular"]}
{"id": "hf-dataset:Narsil/image_dummy", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "Narsil/image_dummy", "date": "2021-08-26", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-08-26", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 216469 downloads.", "popularity": {"value": 216469, "label": "downloads"}, "url": "https://huggingface.co/datasets/Narsil/image_dummy", "tags": ["datasets", "library:datasets", "library:mlcroissant", "modality:audio", "modality:image", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:albertvillanova/datasets-tests-compression", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "albertvillanova/datasets-tests-compression", "date": "2021-08-16", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-08-16", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 67315 downloads.", "popularity": {"value": 67315, "label": "downloads"}, "url": "https://huggingface.co/datasets/albertvillanova/datasets-tests-compression", "tags": ["datasets", "format:json", "library:dask", "library:datasets", "library:mlcroissant", "modality:text", "region:us", "size_categories:n<1k"]}
{"id": "hf-dataset:ttj/metadata_arxiv", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "ttj/metadata_arxiv", "date": "2021-08-05", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-08-05", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 135489 downloads.", "popularity": {"value": 135489, "label": "downloads"}, "url": "https://huggingface.co/datasets/ttj/metadata_arxiv", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "hf-dataset:albertvillanova/tests-raw-jsonl", "source": "Hugging Face Datasets", "sourceId": "huggingface-datasets", "kind": "dataset", "name": "albertvillanova/tests-raw-jsonl", "date": "2021-07-06", "createdAt": "2022-03-02", "sourceUpdatedAt": "2021-07-06", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Hugging Face dataset with 64621 downloads.", "popularity": {"value": 64621, "label": "downloads"}, "url": "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl", "tags": ["datasets", "format:json", "library:datasets", "library:mlcroissant", "library:pandas", "library:polars", "modality:text", "region:us"]}
{"id": "github:dstackai/dstack", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dstackai/dstack", "date": "2026-06-03", "createdAt": "2022-01-04", "sourceUpdatedAt": "2026-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.", "popularity": {"value": 2151, "label": "stars"}, "url": "https://github.com/dstackai/dstack", "tags": ["agents", "inference"]}
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{"id": "github:omriav/blended-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "omriav/blended-diffusion", "date": "2024-06-04", "createdAt": "2021-11-29", "sourceUpdatedAt": "2024-06-04", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Official implementation for \"Blended Diffusion for Text-driven Editing of Natural Images\" [CVPR 2022]", "popularity": {"value": 589, "label": "stars"}, "url": "https://github.com/omriav/blended-diffusion", "tags": ["text-to-image", "tools"]}
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{"id": "github:dingodb/dingo", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "dingodb/dingo", "date": "2026-05-25", "createdAt": "2021-10-14", "sourceUpdatedAt": "2026-05-25", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.", "popularity": {"value": 1701, "label": "stars"}, "url": "https://github.com/dingodb/dingo", "tags": ["vector-database", "vector-db"]}
{"id": "github:mfrashad/text2art", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "mfrashad/text2art", "date": "2023-07-22", "createdAt": "2021-09-28", "sourceUpdatedAt": "2023-07-22", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "AI-powered Text-to-Art Generator - Text2Art.com", "popularity": {"value": 777, "label": "stars"}, "url": "https://github.com/mfrashad/text2art", "tags": ["text-to-image", "tools"]}
{"id": "github:nerdyrodent/clip-guided-diffusion", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "nerdyrodent/CLIP-Guided-Diffusion", "date": "2022-08-29", "createdAt": "2021-09-16", "sourceUpdatedAt": "2022-08-29", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.", "popularity": {"value": 385, "label": "stars"}, "url": "https://github.com/nerdyrodent/CLIP-Guided-Diffusion", "tags": ["developer-tools", "text-to-image"]}
{"id": "github:saharmor/dalle-playground", "source": "GitHub Catalog", "sourceId": "github-catalog", "kind": "repo", "name": "saharmor/dalle-playground", "date": "2024-06-03", "createdAt": "2021-09-13", "sourceUpdatedAt": "2024-06-03", "lastSeenAt": "2026-06-04T03:03:53+00:00", "summary": "A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)", "popularity": {"value": 2744, "label": "stars"}, "url": "https://github.com/saharmor/dalle-playground", "tags": ["text-to-image", "tools"]}
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