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cs.AI2026
Role-Agent: Bootstrapping LLM Agents via Dual-Role Evolution
Xucong Wang, Ziyu Ma, Shidong Yang +4
Although Large Language Model (LLM) agents have demonstrated strong performance on complex tasks, their learning is often limited by inefficient interaction feedback and static tra…
cs.AI2026
SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
Ziyu Ma, Shidong Yang, Yuxiang Ji +5
Large language model (LLM) agents such as OpenClaw rely on reusable skills to perform complex tasks, yet these skills remain largely static after deployment. As a result, similar w…
cs.AI2026
Entropy-Guided Data-Efficient Training for Multimodal Reasoning Reward Models
Shidong Yang, Tongwen Huang, Hao Wen +3
Multimodal reward models are crucial for aligning multimodal large language models with human preferences. Recent works have incorporated reasoning capabilities into these models,…