SOURCE-LINKED INTELLIGENCE
SkillEvoLean: Mutation-enhanced skill evolution for Lean provers
Skill evolution offers a promising way to improve large language model agents without updating their parameters, but its use in formal theorem proving remains underexplored. Existing methods mainly target natural-language reasoning, improving skills by analyzing successful and failed trajectories and incrementally revising solving strategies. Although the Lean verifier provides reliable execution feedback, when all sampled trajectories fail, existing skill evolution methods lack successful trajectories from which to infer effective update directions. Furthermore, these methods also focus mainl
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-10-01T14:42:54.000Z
First collected: 2026-10-02T02:41:42.153Z. This is not the publication date.