Dynamic mutation prompts sampled from a power-law distribution improve the convergence speed of LLaMEA when driven by GPT-4o, but not GPT-3.5-turbo.
Evolutionary computation1(1), 1–23 (1993)
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Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms
Dynamic mutation prompts sampled from a power-law distribution improve the convergence speed of LLaMEA when driven by GPT-4o, but not GPT-3.5-turbo.