Preprint
Jul 2026
Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning
MetaEvolve is presented, a framework designed to develop meta-skills that can transfer broadly to open-ended problems where such rich training signals are scarce, and aims to inspire generalizable domain-agnostic meta-skills that can transfer broadly to open-ended problems where such rich training signals are scarce.
Shujin Wu, Cheng Qian, Xiusi Chen et al.
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