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    SkillRefiner reportedly improves AI agent skills without new rollouts

    An alphaXiv post says the method turns past mistakes into targeted skill edits and checks evidence to avoid drawing the wrong lesson.

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    2 Sources, ,

    TLDR

    An alphaXiv post describes SkillRefiner as a method for refining an agent’s existing skill using historical traces rather than new rollouts. It says repeated successes are reinforced and repeated failures become guardrails, with an evidence check to avoid wrong lessons. The post reports that SkillRefiner improved the original skill in all eight settings, using 1.4–13x fewer refinement tokens than Trace2Skill and 2.4–42x fewer than GEPA.

    Combined views

    48

    2 Sources, first seen 9h ago

    Combined views

    48

    2 Sources, first seen 9h ago

    21 reposts
    9h ago
    first seen 9h ago
    21 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

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    Featured Source

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Today's Rank

    #20

    Today's Rank

    #20

    2 Sources

    @gneubigRT @askalphaxiv: Can agents improve their own skills without generating any new rollouts? This paper introduces SkillRefiner, which learns…9h
    @gregd_nlpRT @AnirudhKhatry: Deployed agents pile up execution traces. The question is whether we can automatically refine skills based on existing r…8h

    2 Sources

    @gneubigRT @askalphaxiv: Can agents improve their own skills without generating any new rollouts? This paper introduces SkillRefiner, which learns…9h
    @gregd_nlpRT @AnirudhKhatry: Deployed agents pile up execution traces. The question is whether we can automatically refine skills based on existing r…8h