# Quantitative Analysis of AI-Generated Texts in Academic Research: A Study of AI Presence in Arxiv Submissions using AI Detection Tool

arXiv: https://arxiv.org/abs/2403.13812 · HTML: https://mlsanity.com/paper/2403.13812/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 23 references that are in the map.
- First posted on arXiv 9 Feb 2024.

## Builds on (most cited first, 4 of 4)

- [COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter](https://mlsanity.com/paper/2005.07503/) (2020)
- [Testing of Detection Tools for AI-Generated Text](https://mlsanity.com/paper/2306.15666/) (2023)
- [Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements](https://mlsanity.com/paper/2001.00623/) (2020)
- [An Empirical Study of AI Generated Text Detection Tools](https://mlsanity.com/paper/2310.01423/) (2023)

## Built on by (most cited first, 3 of 3)

- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [NLLG Quarterly arXiv Report 09/24: What are the most influential current AI Papers?](https://mlsanity.com/paper/2412.12121/) (2024)
- [Most biomedical publications show signs of LLM-assisted writing](https://mlsanity.com/paper/2608.10715/) (2026)

## Abstract (arXiv)

Many people are interested in ChatGPT since it has become a prominent AIGC model that provides high-quality responses in various contexts, such as software development and maintenance. Misuse of ChatGPT might cause significant issues, particularly in public safety and education, despite its immense potential. The majority of researchers choose to publish their work on Arxiv. The effectiveness and originality of future work depend on the ability to detect AI components in such contributions. To address this need, this study will analyze a method that can see purposely manufactured content that academic organizations use to post on Arxiv. For this study, a dataset was created using physics, mathematics, and computer science articles. Using the newly built dataset, the following step is to put originality.ai through its paces. The statistical analysis shows that Originality.ai is very accurate, with a rate of 98%.