arXiv — NLP / Computation & Language · · 3 min read

Most biomedical publications show signs of LLM-assisted writing

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Computer Science > Computation and Language

arXiv:2608.10715 (cs)
[Submitted on 11 Aug 2026]

Title:Most biomedical publications show signs of LLM-assisted writing

View a PDF of the paper titled Most biomedical publications show signs of LLM-assisted writing, by Lena Holzwarth and 2 other authors
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Abstract:Over the past several years, LLM-powered chatbots and agents have become widely used as a tool for academic writing. LLM-assisted writing can be valuable by removing language barriers but at the same time causes concerns about misconduct and fraud. To inform policy decisions, it is necessary to monitor the prevalence of LLM-altered texts in scholarly publications. Despite some recent progress in this direction, no existing method can produce reliable estimates. Here we suggest and validate a new unbiased approach to estimate LLM usage in a corpus of texts based on changing word frequencies. We apply our method to the full texts of open-access biomedical papers from Pubmed Central, and show that by the end of 2025, 89% of papers show excess of LLM-associated vocabulary. We also find that LLMs are twice as likely to be used when writing a paragraph in the Discussion section (68%) compared to a paragraph in the Methods section (32%), but even inside the Methods section, the overall prevalence of LLM usage is over 50%. We believe that our estimates are crucial to shape future guidelines and policies.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Digital Libraries (cs.DL); Social and Information Networks (cs.SI)
Cite as: arXiv:2608.10715 [cs.CL]
  (or arXiv:2608.10715v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2608.10715
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Lena Holzwarth [view email]
[v1] Tue, 11 Aug 2026 09:34:18 UTC (144 KB)
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