Do Self-Evolving Skills Generalize to Held-Out Tasks?
AI agents can externalize what they learn from past tasks into reusable \emph{skills}, such as procedures, checklists, code, or other executable artifacts, that can be retrieved and reused when solving new tasks. Self-evolving skill methods keep rewriting these skills after each round of practice on training tasks, and the skill is then used on new tasks of the same kind. We ask a question: does the improvement a skill shows on its training tasks carry over to new test tasks? We test five self-evolving methods and a one-shot skill on six benchmarks, with the same model, the same agent, and the same train/test split for every method. Of the 21 skills that improve on their training tasks, 5...
| Authors | Xihao Piao, Zifeng Wang, Zhen Chen |
|---|---|
| Primary category | cs.AI |
| Published | 30 September 2026 |
| Last updated at source | 7 October 2026 |
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