# Delving into the Utilisation of ChatGPT in Scientific Publications in Astronomy

arXiv: https://arxiv.org/abs/2406.17324 · HTML: https://mlsanity.com/paper/2406.17324/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 37 references that are in the map.
- First posted on arXiv 25 Jun 2024.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature](https://mlsanity.com/paper/2301.11305/) (2023)
- [Can AI-Generated Text be Reliably Detected?](https://mlsanity.com/paper/2303.11156/) (2023)
- [The Curse of Recursion: Training on Generated Data Makes Models Forget](https://mlsanity.com/paper/2305.17493/) (2023)
- [Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews](https://mlsanity.com/paper/2403.07183/) (2024)
- [Mapping the Increasing Use of LLMs in Scientific Papers](https://mlsanity.com/paper/2404.01268/) (2024)
- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [AstroLLaMA: Towards Specialized Foundation Models in Astronomy](https://mlsanity.com/paper/2309.06126/) (2023)
- [Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?](https://mlsanity.com/paper/2308.01284/) (2023)
- [Differentiate ChatGPT-generated and Human-written Medical Texts](https://mlsanity.com/paper/2304.11567/) (2023)
- [ChatGPT "contamination": estimating the prevalence of LLMs in the scholarly literature](https://mlsanity.com/paper/2403.16887/) (2024)
- [Is ChatGPT Transforming Academics' Writing Style?](https://mlsanity.com/paper/2404.08627/) (2024)
- [Friend or Foe? Exploring the Implications of Large Language Models on the Science System](https://mlsanity.com/paper/2306.09928/) (2023)
- [Towards the relationship between AIGC in manuscript writing and author profiles: evidence from preprints in LLMs](https://mlsanity.com/paper/2404.15799/) (2024)
- [AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets](https://mlsanity.com/paper/2401.01916/) (2024)
- [ADS: The Next Generation Search Platform](https://mlsanity.com/paper/1503.04194/) (2015)

## Built on by (most cited first, 7 of 7)

- [The Impact of Large Language Models in Academia: from Writing to Speaking](https://mlsanity.com/paper/2409.13686/) (2024)
- [Academic journals' AI policies fail to curb the surge in AI-assisted academic writing](https://mlsanity.com/paper/2512.06705/) (2025)
- [What is the Role of Large Language Models in the Evolution of Astronomy Research?](https://mlsanity.com/paper/2409.20252/) (2024)
- [Most biomedical publications show signs of LLM-assisted writing](https://mlsanity.com/paper/2608.10715/) (2026)
- [We Need Improved Data Curation and Attribution in AI for Scientific Discovery](https://mlsanity.com/paper/2504.02486/) (2025)
- [Impact of ChatGPT on the writing style of condensed matter physicists](https://mlsanity.com/paper/2408.17325/) (2024)
- [amc: The Automated Mission Classifier for Telescope Bibliographies](https://mlsanity.com/paper/2512.11202/) (2025)

## Abstract (arXiv)

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.