SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories 事件

SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories arXiv:2606.01311v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on reusable external skills to solve long-horizon interactive tasks. Existing training-free skill adaptation pipelines usually update skills from full trajectories or session-level feedback, which makes failure attribution coarse and often produces unstable or overly broad revisions. We propose SkillAdaptor, a training-free step-