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Delving into the Utilisation of ChatGPT in Scientific Publications in Astronomy

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arxiv 2406.17324 v2 pith:X2KI6Z3C submitted 2024-06-25 cs.CL astro-ph.IMcs.DL

classification cs.CLastro-ph.IMcs.DL
keywords astronomychatgptwordsacademicadoptionidentifylanguagemodels
verification ladder T0 review T1 audit T2 compute T3 formal
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Rapid progress in the capabilities of machine learning approaches in natural language processing has culminated in the rise of large language models over the last two years. Recent works have shown unprecedented adoption of these for academic writing, especially in some fields, but their pervasiveness in astronomy has not been studied sufficiently. To remedy this, we extract words that ChatGPT uses more often than humans when generating academic text and search a total of 1 million articles for them. This way, we assess the frequency of word occurrence in published works in astronomy tracked by the NASA Astrophysics Data System since 2000. We then perform a statistical analysis of the occurrences. We identify a list of words favoured by ChatGPT and find a statistically significant increase for these words against a control group in 2024, which matches the trend in other disciplines. These results suggest a widespread adoption of these models in the writing of astronomy papers. We encourage organisations, publishers, and researchers to work together to identify ethical and pragmatic guidelines to maximise the benefits of these systems while maintaining scientific rigour.

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  1. Most biomedical publications show signs of LLM-assisted writing

    cs.CL 2026-08 conditional novelty 6.0 of 10

    An analysis of 1.19 million biomedical papers estimates that 89% showed signs of LLM-assisted writing by December 2025, using extrapolated word frequencies.

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