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<p>We review how Large Language Models (LLMs) are redefining the scientific method and explore their potential applications across different stages of the scientific cycle, from hypothesis testing to discovery. We conclude that, for LLMs to serve as relevant and effective creative engines and productivity enhancers, their deep integration into all steps of the scientific process should be pursued in collaboration and alignment with human scientific goals, with clear evaluation metrics.</p>

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Exploring the role of large language models in the scientific method: from hypothesis to discovery

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月5日

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  • Yanbo Zhang,
  • Sumeer A. Khan,
  • Adnan Mahmud,
  • Huck Yang,
  • Alexander Lavin,
  • Michael Levin,
  • Jeremy Frey,
  • Jared Dunnmon,
  • James Evans,
  • Alan Bundy,
  • Saso Dzeroski,
  • Jesper Tegner,
  • Hector Zenil

摘要

We review how Large Language Models (LLMs) are redefining the scientific method and explore their potential applications across different stages of the scientific cycle, from hypothesis testing to discovery. We conclude that, for LLMs to serve as relevant and effective creative engines and productivity enhancers, their deep integration into all steps of the scientific process should be pursued in collaboration and alignment with human scientific goals, with clear evaluation metrics.