-
Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
Paper • 2603.25158 • Published • 50 -
SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
Paper • 2604.08377 • Published • 278 -
How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings
Paper • 2604.04323 • Published • 40 -
SkillX: Automatically Constructing Skill Knowledge Bases for Agents
Paper • 2604.04804 • Published • 32
Collections
Discover the best community collections!
Collections including paper arxiv:2604.04804
-
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Paper • 2603.12056 • Published • 33 -
Memento-Skills: Let Agents Design Agents
Paper • 2603.18743 • Published • 57 -
SWE-Skills-Bench: Do Agent Skills Actually Help in Real-World Software Engineering?
Paper • 2603.15401 • Published • 19 -
Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
Paper • 2603.25158 • Published • 50
-
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 107 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 80 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 43 -
Matryoshka Diffusion Models
Paper • 2310.15111 • Published • 45
-
dLLM: Simple Diffusion Language Modeling
Paper • 2602.22661 • Published • 152 -
OpenSeeker: Democratizing Frontier Search Agents by Fully Open-Sourcing Training Data
Paper • 2603.15594 • Published • 149 -
Qianfan-OCR: A Unified End-to-End Model for Document Intelligence
Paper • 2603.13398 • Published • 153 -
Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders
Paper • 2603.06569 • Published • 119
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 259 • 99 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 39 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
Paper • 2603.25158 • Published • 50 -
SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
Paper • 2604.08377 • Published • 278 -
How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings
Paper • 2604.04323 • Published • 40 -
SkillX: Automatically Constructing Skill Knowledge Bases for Agents
Paper • 2604.04804 • Published • 32
-
dLLM: Simple Diffusion Language Modeling
Paper • 2602.22661 • Published • 152 -
OpenSeeker: Democratizing Frontier Search Agents by Fully Open-Sourcing Training Data
Paper • 2603.15594 • Published • 149 -
Qianfan-OCR: A Unified End-to-End Model for Document Intelligence
Paper • 2603.13398 • Published • 153 -
Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders
Paper • 2603.06569 • Published • 119
-
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Paper • 2603.12056 • Published • 33 -
Memento-Skills: Let Agents Design Agents
Paper • 2603.18743 • Published • 57 -
SWE-Skills-Bench: Do Agent Skills Actually Help in Real-World Software Engineering?
Paper • 2603.15401 • Published • 19 -
Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
Paper • 2603.25158 • Published • 50
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 259 • 99 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 39 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 107 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 80 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 43 -
Matryoshka Diffusion Models
Paper • 2310.15111 • Published • 45