@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://aclanthology.org/2025.findings-acl.987/",
doi = "10.18653/v1/2025.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."
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%0 Conference Proceedings
%T The Impact of Large Language Models in Academia: from Writing to Speaking
%A Geng, Mingmeng
%A Chen, Caixi
%A Wu, Yanru
%A Wan, Yao
%A Zhou, Pan
%A Chen, Dongping
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F geng-etal-2025-impact
%X 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.
%R 10.18653/v1/2025.findings-acl.987
%U https://aclanthology.org/2025.findings-acl.987/
%U https://doi.org/10.18653/v1/2025.findings-acl.987
%P 19303-19319
Markdown (Informal)
[The Impact of Large Language Models in Academia: from Writing to Speaking](https://aclanthology.org/2025.findings-acl.987/) (Geng et al., Findings 2025)
ACL