# Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers

arXiv: https://arxiv.org/abs/2603.25638 · HTML: https://mlsanity.com/paper/2603.25638/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 48 references that are in the map.
- First posted on arXiv 26 Mar 2026.

## Builds on (most cited first, 30 of 30)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders](https://mlsanity.com/paper/2404.05961/) (2024)
- [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)
- [Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)](https://mlsanity.com/paper/2510.22954/) (2025)
- [A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions](https://mlsanity.com/paper/2310.14724/) (2023)
- [Model Equality Testing: Which Model Is This API Serving?](https://mlsanity.com/paper/2410.20247/) (2024)
- [LLMDet: A Third Party Large Language Models Generated Text Detection Tool](https://mlsanity.com/paper/2305.15004/) (2023)
- [Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://mlsanity.com/paper/2502.05151/) (2025)
- [People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://mlsanity.com/paper/2501.15654/) (2025)
- [Your Large Language Models Are Leaving Fingerprints](https://mlsanity.com/paper/2405.14057/) (2024)
- [Scientific production in the era of Large Language Models](https://mlsanity.com/paper/2601.13187/) (2026)
- [Stopwords in Technical Language Processing](https://mlsanity.com/paper/2006.02633/) (2020)
- [From Text to Source: Results in Detecting Large Language Model-Generated Content](https://mlsanity.com/paper/2309.13322/) (2023)
- [Is ChatGPT Transforming Academics' Writing Style?](https://mlsanity.com/paper/2404.08627/) (2024)
- [How LLMs Distort Our Written Language](https://mlsanity.com/paper/2603.18161/) (2026)
- [HalluCitation Matters: Revealing the Impact of Hallucinated References with 300 Hallucinated Papers in ACL Conferences](https://mlsanity.com/paper/2601.18724/) (2026)
- [Model Provenance Testing for Large Language Models](https://mlsanity.com/paper/2502.00706/) (2025)
- [Human-LLM Coevolution: Evidence from Academic Writing](https://mlsanity.com/paper/2502.09606/) (2025)
- [LLM as a Broken Telephone: Iterative Generation Distorts Information](https://mlsanity.com/paper/2502.20258/) (2025)
- [Academic journals' AI policies fail to curb the surge in AI-assisted academic writing](https://mlsanity.com/paper/2512.06705/) (2025)
- [How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices?](https://mlsanity.com/paper/2504.02767/) (2025)
- [Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humans](https://mlsanity.com/paper/2308.07462/) (2023)
- [Why Does ChatGPT "Delve" So Much? Exploring the Sources of Lexical Overrepresentation in Large Language Models](https://mlsanity.com/paper/2412.11385/) (2024)
- [Examining Linguistic Shifts in Academic Writing Before and After the Launch of ChatGPT: A Study on Preprint Papers](https://mlsanity.com/paper/2505.12218/) (2025)
- [Estimating the prevalence of LLM-assisted text in scholarly writing](https://mlsanity.com/paper/2512.01560/) (2025)
- [On the Detectability of LLM-Generated Text: What Exactly Is LLM-Generated Text?](https://mlsanity.com/paper/2510.20810/) (2025)
- [Large language models reshape the language of science](https://mlsanity.com/paper/2504.12317/) (2025)
- [Who Gets Seen in the Age of AI? Adoption Patterns of Large Language Models in Scholarly Writing and Citation Outcomes](https://mlsanity.com/paper/2509.08306/) (2025)
- [Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing](https://mlsanity.com/paper/2511.12529/) (2025)

## Built on by (most cited first, 1 of 1)

- [AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing](https://mlsanity.com/paper/2605.25358/) (2026)

## Abstract (arXiv)

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 differences between models and prompts, we quantitatively assess these effects and show that real-world LLM usage is heterogeneous and dynamic.