@inproceedings{geng-etal-2025-impact,
    title = "The Impact of Large Language Models in Academia: from Writing to Speaking",
    author = "Geng, Mingmeng  and
      Chen, Caixi  and
      Wu, Yanru  and
      Wan, Yao  and
      Zhou, Pan  and
      Chen, Dongping",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/display_plenaries/2025.findings-acl.987/",
    pages = "19303--19319",
    ISBN = "979-8-89176-256-5",
    abstract = "Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine learning conferences, we examined and compared the words used in writing and speaking, representing the first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people. Our empirical results show that LLM-style words such as significant have been used more frequently in abstracts and oral presentations. The implicit impact on human expression like writing and speaking is beginning to emerge and is likely to grow in the future. We take the first step in building an automated monitoring platform to record its longitudinal changes to call attention to the implicit influence and ripple effect of LLMs on human society."
}