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Quantifying large language model usage in scientific papers.

Weixin Liang1, Yaohui Zhang2, Zhengxuan Wu3

  • 1Department of Computer Science, Stanford University, Stanford, CA, USA. wxliang@stanford.edu.

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This summary is machine-generated.

Large language models (LLMs) are increasingly used in scientific writing. Analysis of over a million papers shows a steady rise in LLM modification, especially in computer science.

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Area of Science:

  • Scientific publishing
  • Academic writing
  • Research dissemination

Background:

  • Speculation exists regarding the extent of large language model (LLM) adoption in academic writing.
  • Scientific publishing is crucial for sharing research findings.

Purpose of the Study:

  • To systematically analyze the prevalence of LLM-modified content in scientific papers.
  • To track the trends and growth of LLM usage in academic writing over time.

Main Methods:

  • Analysis of 1,121,912 preprints and published papers from January 2020 to September 2024.
  • Utilized a population-level framework based on word frequency shifts to estimate LLM modification.
  • Data sources included arXiv, bioRxiv, and Nature portfolio journals.

Main Results:

  • A steady increase in LLM usage was observed across scientific disciplines.
  • Computer science papers showed the largest and fastest growth in LLM modification, up to 22%.
  • Mathematics papers and Nature portfolio journals exhibited lower LLM modification rates (up to 9%).
  • Higher LLM modification estimates correlated with frequent preprint posting by first authors, crowded research areas, and shorter paper lengths.

Conclusions:

  • LLMs are being broadly adopted and utilized in scientific writing.
  • The findings highlight a significant and growing trend of LLM integration in research dissemination.
  • Disciplinary and author-specific factors influence the rate of LLM modification in scientific publications.