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Quantifying Large Language Model Usage In Scientific Papers Weixin Liang Yaohui Zhang Zhengxuan Wu Haley Lepp Wenlong Ji Xuandong Zhao Hancheng Cao Sheng Liu Siyu He Zhi Huang Diyi Yang Christopher Potts Christopher D Manning James Zou

  • SKU: BELL-237800262
Quantifying Large Language Model Usage In Scientific Papers Weixin Liang Yaohui Zhang Zhengxuan Wu Haley Lepp Wenlong Ji Xuandong Zhao Hancheng Cao Sheng Liu Siyu He Zhi Huang Diyi Yang Christopher Potts Christopher D Manning James Zou
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Quantifying Large Language Model Usage In Scientific Papers Weixin Liang Yaohui Zhang Zhengxuan Wu Haley Lepp Wenlong Ji Xuandong Zhao Hancheng Cao Sheng Liu Siyu He Zhi Huang Diyi Yang Christopher Potts Christopher D Manning James Zou instant download after payment.

Publisher: x
File Extension: PDF
File size: 1.46 MB
Author: Weixin Liang & Yaohui Zhang & Zhengxuan Wu & Haley Lepp & Wenlong Ji & Xuandong Zhao & Hancheng Cao & Sheng Liu & Siyu He & Zhi Huang & Diyi Yang & Christopher Potts & Christopher D. Manning & James Zou
Language: English
Year: 2025

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Quantifying Large Language Model Usage In Scientific Papers Weixin Liang Yaohui Zhang Zhengxuan Wu Haley Lepp Wenlong Ji Xuandong Zhao Hancheng Cao Sheng Liu Siyu He Zhi Huang Diyi Yang Christopher Potts Christopher D Manning James Zou by Weixin Liang & Yaohui Zhang & Zhengxuan Wu & Haley Lepp & Wenlong Ji & Xuandong Zhao & Hancheng Cao & Sheng Liu & Siyu He & Zhi Huang & Diyi Yang & Christopher Potts & Christopher D. Manning & James Zou instant download after payment.

Nature Human Behaviour, doi:10.1038/s41562-025-02273-8

Scientifc publishing is the primary means of disseminating research fndings. There has been speculation about how extensively large language models (LLMs) are being used in academic writing. Here we conduct a systematic analysis across 1,121,912 preprints and published papers from January 2020 to September 2024 on arXiv, bioRxiv and Nature portfolio journals, using a population-level framework based on word frequency shifts to estimate the prevalence of LLM-modifed content over time. Our fndings suggest a steady increase in LLM usage, with the largest and fastest growth estimated for computer science papers (up to 22%). By comparison, mathematics papers and the Nature portfolio showed lower evidence of LLM modifcation (up to 9%). LLM modifcation estimates were higher among papers from frst authors who post preprints more frequently, papers in more crowded research areas and papers of shorter lengths. Our fndings suggest that LLMs are being broadly used in scientifc writing.