Quantitative Analysis of AI-Generated Texts in Academic Research: A
  Study of AI Presence in Arxiv Submissions using AI Detection Tool
Arslan Akram
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%.