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EvoMem: Memory-Augmented Evolution for Code Optimization

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Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may transfer across related tasks and domains. However, existing LLM-driven evolutionary frameworks largely discard such knowledge, repeatedly rediscovering similar ideas and limiting opportunities for cross-run and cross-task learning.

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EvoMem: Memory-Augmented Evolution for Code Optimization

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