Machine-generated Text Detection
Machine-Generated Text Detection is an academic research contribution that, within the domain of academic integrity detection, constitutes a methodological framework designed to identify textual content produced by artificial intelligence systems as distinct from human-authored text.
200
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13.2K
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742
Authors
309
Institutions
Publications per year
2017–2026
173
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200
Ismail Dergaa, Karim Chamari, Piotr Żmijewski et al. · Biology of Sport · 2023 · 741 citations · Full text
GPT detectors are biased against non-native English writers
Weixin Liang, Mert Yüksekgönül, Yining Mao et al. · Patterns · 2023 · 457 citations · Full text
Catherine A. Gao, Frederick M. Howard, Nikolay S. Markov et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2022 · 414 citations · Full text
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Cornell University
Ithaca, United States
7 h-index
9 publications
837 citations
James Cook University Singapore
Singapore, Singapore
4 h-index
4 publications
335 citations
British University Vietnam
Hanoi, Vietnam
4 h-index
12 publications
1.2K citations
Queen Mary University of London
London, United Kingdom
3 h-index
3 publications
554 citations
University of Technology Malaysia
Johor Bahru, Malaysia
3 h-index
5 publications
94 citations
University of Chicago
Chicago, United States
3 h-index
9 publications
4.3K citations
Northwestern University
Evanston, United States
3 h-index
5 publications
2.1K citations
Fudan University
Shanghai, China
3 h-index
8 publications
325 citations
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Repository · 38 publications · 1.6K citations
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5 publications · 922 citations
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5 publications · 381 citations
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Conference · 4 publications · 259 citations
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4 publications · 141 citations
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