mlsanityData to 14 Oct 2026

Human-LLM Coevolution: Evidence from Academic Writing

arXiv 2502.09606 ↗First posted 13 Feb 2025cs.CL cs.AI cs.CYcited by 15

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Abstract (arXiv)

With a statistical analysis of arXiv paper abstracts, we report a marked drop in the frequency of several words previously identified as overused by ChatGPT, such as "delve", starting soon after they were pointed out in early 2024. The frequency of certain other words favored by ChatGPT, such as "significant", has instead kept increasing. These phenomena suggest that some authors of academic papers have adapted their use of large language models (LLMs), for example, by selecting outputs or applying modifications to the LLM-generated content. Such coevolution and cooperation of humans and LLMs thus introduce additional challenges to the detection of machine-generated text in real-world scenarios. Estimating the impact of LLMs on academic writing by examining word frequency remains feasible, and more attention should be paid to words that were already frequently employed, including those that have decreased in frequency due to LLMs' disfavor.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Builds on 20 of its 29 references that are in the map. First posted on arXiv 13 Feb 2025.

Builds on

20 of 29 references.

References · 20

  1. 2023Can AI-Generated Text be Reliably Detected?cited by 386
  2. 2024Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Textcited by 263
  3. 2024Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviewscited by 164
  4. 2023The Science of Detecting LLM-Generated Textscited by 128
  5. 2024Mapping the Increasing Use of LLMs in Scientific Paperscited by 118
  6. 2023Testing of Detection Tools for AI-Generated Textcited by 90
  7. 2024LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?cited by 49
  8. 2024LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptionscited by 47
  9. 2025People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textcited by 40
  10. 2023Towards Possibilities & Impossibilities of AI-generated Text Detection: A Surveycited by 28
  11. 2024Stumbling Blocks: Stress Testing the Robustness of Machine-Generated Text Detectors Under Attackscited by 26
  12. 2024ChatGPT "contamination": estimating the prevalence of LLMs in the scholarly literaturecited by 26
8 more
  1. 2024The Impact of Large Language Models in Academia: from Writing to Speakingcited by 18
  2. 2024Exploring the Limitations of Detecting Machine-Generated Textcited by 15
  3. 2024Towards the relationship between AIGC in manuscript writing and author profiles: evidence from preprints in LLMscited by 14
  4. 2025GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Humancited by 13
  5. 2024WithdrarXiv: A Large-Scale Dataset for Retraction Studycited by 9
  6. 2023Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humanscited by 8
  7. 2024GenAI Content Detection Task 2: AI vs. Human -- Academic Essay Authenticity Challengecited by 6
  8. 2024NLLG Quarterly arXiv Report 09/24: What are the most influential current AI Papers?cited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 10.

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