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arXiv:2601.13187cs.DL

Scientific production in the era of Large Language Models

Keigo Kusumegi, Xinyu Yang, Paul Ginsparg, Mathijs de Vaan, Toby Stuart, Yian Yin

Abstract

Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and 246M online accesses to scientific documents. We find: 1) scientists adopting LLMs to draft manuscripts demonstrate a large increase in paper production, ranging from 23.7-89.3% depending on scientific field and author background, 2) LLM use has reversed the relationship between writing complexity and paper quality, leading to an influx of manuscripts that are linguistically complex but substantively underwhelming, and 3) LLM adopters access and cite more diverse prior work, including books and younger, less-cited documents. These findings highlight a stunning shift in scientific production that will likely require a change in how journals, funding agencies, and tenure committees evaluate scientific works.

arXiv comments
This is the author's version of the work. The definitive version was published in Science on 18 Dec 2025, DOI: 10.1126/science.adw3000. Link to the Final Published Version: https://www.science.org/doi/10.1126/science.adw3000
Journal reference
Science, 390(6779), pp.1240-1243 (2025)
DOI
doi:10.1126/science.adw3000
Subjects
cs.DLDigital Libraries cs.AIArtificial Intelligence cs.CYComputers and Society physics.soc-phPhysics and Society

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    • several authors including the creator of arxiv, Paul Ginsparg, foretell a future in which we "increasingly rely on status markers such as author pedigree and institutional affiliation as signals of quality, ironically counteracting the democratizing effects of LLMs on scientific…

      lhd1View on HNParent context

  1. Science Is Drowning in AI Slop 1 comment
    • AI causes just an intensification of longstanding problems. The "publish or perish" pressure has compromised research integrity for decades (including manipulated peer reviews, massaged or fabricated results, and ignored conflicts of interest). Cambridge University Press…

      RochusView on HNParent context

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