AI RESEARCH
EvoX: Meta-Evolution for Automated Discovery
arXiv CS.LG
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ArXi:2602.23413v2 Announce Type: replace Recent work such as AlphaEvolve has shown that combining LLM-driven optimization with evolutionary search can effectively improve programs, prompts, and algorithms across domains. In this paradigm, previously evaluated solutions are reused to guide the model toward new candidate solutions. Crucially, the effectiveness of this evolution process depends on the search strategy: how prior solutions are selected and varied to generate new candidates.