AI RESEARCH
Training Language Agents to Learn from Experience
arXiv CS.LG
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ArXi:2605.20477v1 Announce Type: new Language agents can adapt from experience in interactive environments, but current reflection-based methods can only self-correct within a single task instance. Whether such experience can be distilled into reusable lessons that improve performance on future unseen tasks remains unclear. We address this problem by