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AXXX, Moscow, Russia, Lomonosov Moscow State University, Moscow, Russia
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Persistent memory in EvoMem reduces redundant exploration in evolutionary code search, leading to faster and more effective optimization across multiple tasks.
Explicit supervision of failed reasoning branches boosts model recovery rates, leading to a dramatic 72.7 percentage point improvement in solving hidden graph tasks.
