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The impact of AI language models on scientific writing and scientific peer reviews: A Systematic Literature Review

  • Rand Alchokr
  • , Evelyn Starzew
  • , Gunter Saake
  • , Thomas Leich
  • , Jacob Krüger

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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Samenvatting

Recent advances in deep learning have led to the development of well-known AI language models, such as ChatGPT. Such models have gained widespread attention across various domains, including scientific research. In this context, discussions about the use of these models for writing and reviewing publications have started. Within this paper, we discuss the implications of integrating AI language models into the scientific writing process and provide a comprehensive overview of existing research on this topic. Therefore, we searched, describe, summarize, and organize existing research following systematic literature-review guidelines using the digital library Scopus. Since peer review is a crucial part of scientific research, we also focus on exploring the consequent impact of emerging models on the peer-reviewing process. Existing studies show that AI language models are used significantly in scientific writing. However, this usage requires guidelines and control to overcome potential challenges and problems.

Originele taal-2Engels
TitelJCDL 2024 - Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries
RedacteurenJian Wu, Xiao Hu, Terhi Nurmikko-Fuller, Sam Chu, Ruixian Yang, J. Stephen Downie
UitgeverijAssociation for Computing Machinery, Inc.
Aantal pagina's6
ISBN van elektronische versie9798400710933
DOI's
StatusGepubliceerd - 13 mrt. 2025
Evenement24th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2024 - Hong Kong, Hongkong
Duur: 16 dec. 202420 dec. 2024

Congres

Congres24th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2024
Land/RegioHongkong
StadHong Kong
Periode16/12/2420/12/24

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© 2024 Copyright held by the owner/author(s).

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