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DiagEvo: Diagnosis-Guided Self-Evolution via Hierarchical Error Memory

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Self-play is an effective paradigm for language-model self-evolution, but without guidance, solver performance can plateau or decline across rounds. Unguided methods steer question generation with signals such as difficulty, learnability, or diversity. These signals keep questions challenging and varied but do not specify which unresolved reasoning weaknesses later rounds should target. Guided methods obtain direction from external task resources, including human examples, document corpora, or specified difficulty targets, and therefore rely on task information supplied outside the self-play l

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