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

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arxiv 2403.13812 v1 pith:HO2GMJ6C submitted 2024-02-09 cs.DL cs.AIcs.CLcs.CYcs.LGstat.OT

Arslan Akram This is my paper · ORCID
classification cs.DLcs.AIcs.CLcs.CYcs.LGstat.OT
keywords arxivoriginalityacademicanalysischatgptdatasetworkability
verification ladder T0 review T1 audit T2 compute T3 formal
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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%.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Most biomedical publications show signs of LLM-assisted writing

    cs.CL 2026-08 conditional novelty 6.0 of 10

    An analysis of 1.19 million biomedical papers estimates that 89% showed signs of LLM-assisted writing by December 2025, using extrapolated word frequencies.

  2. NLLG Quarterly arXiv Report 09/24: What are the most influential current AI Papers?

    cs.DL 2024-12 conditional novelty 4.0 of 10

    A quarterly bibliometric report identifies the top-40 most influential AI arXiv papers of 2023-2024 and finds that they show fewer AI-generated text markers than random papers.

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