LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization

• URL: http://arxiv.org/abs/2306.01102v7
• Date: Wed, 10 Apr 2024 13:18:37 GMT
• Title: LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization
• Authors: Muhammad U. Nasir, Sam Earle, Julian Togelius, Steven James, Christopher Cleghorn,
• Abstract summary: Large Language Models (LLMs) have emerged as powerful tools capable of accomplishing a broad spectrum of tasks. We propose using the coding abilities of LLMs to introduce meaningful variations to code defining neural networks. By merging the code-generating abilities of LLMs with the diversity and robustness of QD solutions, we introduce textttLLMatic, a Neural Architecture Search (NAS) algorithm.
• Score: 4.951599300340954
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) have emerged as powerful tools capable of accomplishing a broad spectrum of tasks. Their abilities span numerous areas, and one area where they have made a significant impact is in the domain of code generation. Here, we propose using the coding abilities of LLMs to introduce meaningful variations to code defining neural networks. Meanwhile, Quality-Diversity (QD) algorithms are known to discover diverse and robust solutions. By merging the code-generating abilities of LLMs with the diversity and robustness of QD solutions, we introduce \texttt{LLMatic}, a Neural Architecture Search (NAS) algorithm. While LLMs struggle to conduct NAS directly through prompts, \texttt{LLMatic} uses a procedural approach, leveraging QD for prompts and network architecture to create diverse and high-performing networks. We test \texttt{LLMatic} on the CIFAR-10 and NAS-bench-201 benchmarks, demonstrating that it can produce competitive networks while evaluating just $2,000$ candidates, even without prior knowledge of the benchmark domain or exposure to any previous top-performing models for the benchmark. The open-sourced code is available in \url{https://github.com/umair-nasir14/LLMatic}.

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