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The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts.
Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, et al. 2019 · 1908
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Modification of the coleman readability formulas
Ta Lin Liau, Carolyn B Bassin, Clessen J Martin, and Edmund B Coleman. 1976 · 1976
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The neurocognition of syntactic processing
Peter Hagoort, Colin M Brown, and Lee Osterhout. 1999 · 1999
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Kruskal-wallis test
Patrick E McKight and Julius Najab. 2010 · 2010
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Authorship attribution with latent dirichlet allocation
Yanir Seroussi, Ingrid Zukerman, and Fabian Bohnert. 2011 · 2011
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Crowdsourcing a word-emotion association lexicon
Saif M. Mohammad and Peter D. Turney. 2013 · 2013
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Towards a general rule for identifying deceptive opinion spam
Jiwei Li, Myle Ott, Claire Cardie, and Eduard Hovy. 2014 · 2014
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Authorship attribution with topic models
Yanir Seroussi, Ingrid Zukerman, and Fabian Bohnert. 2014 · 2014
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Nonparametric pairwise multiple comparisons in independent groups using dunn’s test
Alexis Dinno. 2015 · 2015
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Leveraging discourse information effectively for authorship attribution
Elisa Ferracane, Su Wang, and Raymond Mooney. 2017 · 2017
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Abhay Sharma, Ananya Nandan, and Reetika Ralhan. 2018 · 2018
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Register, genre, and style
Douglas Biber and Susan Conrad. 2019 · 2019
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GLTR: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Automatic detection of generated text is easiest when humans are fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck. 2020 · 2020
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Automatic detection of machine generated text: A critical survey
Ganesh Jawahar, Muhammad Abdul-Mageed, and Laks Lakshmanan, V.S. 2020 · 2020
Cited alongside, same era.
Authorship attribution for neural text generation
Free dolly: Introducing the world’s first truly open instruction-tuned llm
Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin. 2023 · 2023
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Machine-generated text: A comprehensive survey of threat models and detection methods
Evan N Crothers, Nathalie Japkowicz, and Herna L Viktor. 2023 · 2023
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Real or fake text?: Investigating human ability to detect boundaries between human-written and machine-generated text
Liam Dugan, Daphne Ippolito, Arun Kirubarajan, Sherry Shi, and Chris Callison-Burch. 2023 · 2023
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How close is chatgpt to human experts? comparison corpus, evaluation, and detection
Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, and Yupeng Wu. 2023 · 2023
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Stylometric detection of ai-generated text in twitter timelines
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Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee. 2020 · 2020
Cited alongside, same era.
Automating creativity assessment with semdis: An open platform for computing semantic distance
Roger E Beaty and Dan R Johnson. 2021 · 2021
Cited alongside, same era.
A benchmark dataset to distinguish human-written and machine-generated scientific papers
Mohamed Hesham Ibrahim Abdalla, Simon Malberg, Daryna Dementieva, Edoardo Mosca, and Georg Groh. 2023 · 2023
Cited alongside, same era.
Leia: Linguistic embeddings for the identification of affect
Segun Taofeek Aroyehun, Lukas Malik, Hannah Metzler, Nikolas Haimerl, Anna Di Natale, and David Garcia. 2023 · 2023
Cited alongside, same era.
Using chatgpt for second language writing: Pitfalls and potentials
Jessie S. Barrot. 2023 · 2023
Cited alongside, same era.
M4: Multi-generator, multi-domain, and multi-lingual black-box machine-generated text detection
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Chenxi Whitehouse, Osama Mohammed Afzal, Tarek Mahmoud, Toru Sasaki, Thomas Arnold, Alham Aji, Nizar Habash, Iryna Gurevych, and Preslav Nakov. 2024b
Cited in the paper.
Tharindu Kumarage, Joshua Garland, Amrita Bhattacharjee, Kirill Trapeznikov, Scott Ruston, and Huan Liu. 2023 · 2023
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LFTK: Handcrafted features in computational linguistics
Bruce W. Lee and Jason Lee. 2023 · 2023
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Ai vs. human–differentiation analysis of scientific content generation
Yongqiang Ma, Jiawei Liu, Fan Yi, Qikai Cheng, Yong Huang, Wei Lu, and Xiaozhong Liu. 2023 · 2023
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Detectgpt: Zero-shot machine-generated text detection using probability curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D Manning, and Chelsea Finn. 2023 · 2023
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Crosslingual generalization through multitask finetuning
Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, and Colin Raffel. 2023 · 2023
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Semeval-2024 task 8: Multidomain, multimodel and multilingual machine-generated text detection
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, jinyan su, Artem Shelmanov, Akim Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Chenxi Whitehouse, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, and Preslav Nakov. 2024a · 2063
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