6 papers
Progressive Agent Skill Generation via Reinforcement Learning
Junhao Shen, Zhanqiu Zhang, Yiwen Guo +1
Recent large language model agents often use external skills as modular procedural units that condition inference and improve complex task solving. Thus, automatically generating h…
Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design
Qing Zong, Jiayu Liu, Junhao Shen +9
Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedb…
Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning
Junhao Shen, Teng Zhang, Xiaoyan Zhao +1
Large language model agents increasingly rely on external skills to solve complex tasks, where skills act as modular units that extend their capabilities beyond what parametric mem…
Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving
Yuzhe Gu, Songyang Gao, Zijian Wu +18
Large Reasoning Models (LRMs) have expanded the mathematical reasoning frontier through Chain-of-Thought (CoT) techniques and Reinforcement Learning with Verifiable Rewards (RLVR),…
Achieving Olympiad-Level Geometry Large Language Model Agent via Complexity Boosting Reinforcement Learning
Haiteng Zhao, Junhao Shen, Yiming Zhang +7
Large language model (LLM) agents exhibit strong mathematical problem-solving abilities and can even solve International Mathematical Olympiad (IMO) level problems with the assista…
Semi-off-Policy Reinforcement Learning for Vision-Language Slow-Thinking Reasoning
Junhao Shen, Haiteng Zhao, Yuzhe Gu +7
Enhancing large vision-language models (LVLMs) with visual slow-thinking reasoning is crucial for solving complex multimodal tasks. However, since LVLMs are mainly trained with vis…