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We find that large language models (LLMs) are more likely to modify human-written text than AI-generated text when tasked with rewriting.
Application of the logistic function to bio-assay
Joseph Berkson · 1944
Earlier work this paper cites.
Binary codes capable of correcting deletions, insertions, and reversals
Vladimir I Levenshtein · 1966
Earlier work this paper cites.
Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
Earlier work this paper cites.
Real or fake? learning to discriminate machine from human generated text
Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc’Aurelio Ranzato, and Arthur Szlam · 2019
Earlier work this paper cites.
Gltr: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M Rush · 2019
Earlier work this paper cites.
Automatic detection of generated text is easiest when humans are fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck · 2019
Earlier work this paper cites.
Is bert really robust? natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Automatic detection of machine generated text: A critical survey
Ganesh Jawahar, Muhammad Abdul-Mageed, and Laks VS Lakshmanan · 2020
Earlier work this paper cites.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba · 2021
Earlier work this paper cites.
Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A Smith, and Yejin Choi · 2021
Earlier work this paper cites.
Tweepfake: About detecting deepfake tweets
Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi · 2021
Earlier work this paper cites.
Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
Earlier work this paper cites.
Guiding the release of safer e2e conversational ai through value sensitive design
A Stevie Bergman, Gavin Abercrombie, Shannon Spruit, Dirk Hovy, Emily Dinan, Y-Lan Boureau, Verena Rieser, et al · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Cited alongside, same era.
Pretrained language models for text generation: A survey
Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen · 2022
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The threat of offensive ai to organizations
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Deng Gelei, Liu Yang, Xiangyu Zhang, Maura Pintor, Wenke Lee, Yuval Elovici, et al · 2022
Exploiting programmatic behavior of llms: Dual-use through standard security attacks
Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, and Tatsunori Hashimoto · 2023
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A watermark for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein · 2023
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Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, and Mohit Iyyer · 2023
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Gpt detectors are biased against non-native english writers
Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu, and James Zou · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Asleep at the keyboard? assessing the security of github copilot’s code contributions
Hammond Pearce, Baleegh Ahmad, Benjamin Tan, Brendan Dolan-Gavitt, and Ramesh Karri · 2022
Cited alongside, same era.
An empirical study of code smells in transformer-based code generation techniques
Mohammed Latif Siddiq, Shafayat H Majumder, Maisha R Mim, Sourov Jajodia, and Joanna CS Santos · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
Cited alongside, same era.
Large language models are human-level prompt engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba · 2022
Cited alongside, same era.
URL https://chat.openai.com
Chatgpt: Optimizing language models for dialogue, 2023 · 2023
Cited alongside, same era.
URL https://www.anthropic.com/product
Anthropic, 2023 · 2023
Cited alongside, same era.
Fatemehsadat Mireshghallah, Justus Mattern, Sicun Gao, Reza Shokri, and Taylor Berg-Kirkpatrick · 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
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On the risk of misinformation pollution with large language models
Yikang Pan, Liangming Pan, Wenhu Chen, Preslav Nakov, Min-Yen Kan, and William Yang Wang · 2023
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Robust speech recognition via large-scale weak supervision
Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever · 2023
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Can ai-generated text be reliably detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi · 2023
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The curse of recursion: Training on generated data makes models forget
Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson · 2023
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The science of detecting llm-generated texts
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu · 2023
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URL https://gptzero.me
E Tian, 2023 · 2023
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Ghostbuster: Detecting text ghostwritten by large language models
Vivek Verma, Eve Fleisig, Nicholas Tomlin, and Dan Klein · 2023
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Recurrentgpt: Interactive generation of (arbitrarily) long text
Wangchunshu Zhou, Yuchen Eleanor Jiang, Peng Cui, Tiannan Wang, Zhenxin Xiao, Yifan Hou, Ryan Cotterell, and Mrinmaya Sachan · 2023
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson · 2023
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