MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation 事件

MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation arXiv:2605.27366v1 Announce Type: cross Abstract: Large language model (LLM) agents rely on reusable skills to solve complex tasks. However, existing skill creation approaches treat skills as isolated and static artifacts, limiting their reusability, reliability, and long-term improvement. We propose MUSE-Autoskill Agent (Memory-Utilizing Skill Evolution), a skill-centric agent framework that lets agents