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.
@article{arxiv.2601.13187,
title = {Scientific production in the era of Large Language Models},
author = {Keigo Kusumegi and Xinyu Yang and Paul Ginsparg and Mathijs de Vaan and Toby Stuart and Yian Yin},
journal= {arXiv preprint arXiv:2601.13187},
year = {2026}
}
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