Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers
Through an analysis of arXiv papers, we report several shifts in word usage that are likely driven by large language models (LLMs) but have not previously received sufficient attention, such as the increased frequency of "beyond" and "via" in titles and the decreased frequency of "the" and "of" in abstracts. Due to the similarities among different LLMs, experiments show that current classifiers struggle to accurately determine which specific model generated a given text in multi-class classification tasks. Meanwhile, variations across LLMs also result in evolving patterns of word usage in academic papers. By adopting a direct and highly interpretable linear approach and accounting for dif...
| Authors | Mingmeng Geng, Yuhang Dong, Thierry Poibeau |
|---|---|
| Primary category | cs.CL |
| Published | 26 March 2026 |
| Last updated at source | 2 April 2026 |
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