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Watermarking of language model outputs enables statistical detection of model-generated text, which can mitigate harms and misuses of language models.
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 · 1906
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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 · 1908
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Watermarking the outputs of structured prediction with an application in statistical machine translation
Ashish Venugopal, Jakob Uszkoreit, David Talbot, Franz Och, and Juri Ganitkevitch · 2011
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Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Yoon Kim and Alexander M. Rush · 2016
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A review of text watermarking: Theory, methods, and applications
Nurul Shamimi Kamaruddin, Amirrudin Kamsin, Lip Yee Por, and Hameedur Rahman · 2018
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GLTR: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush · 2019
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Openwebtext corpus
Aaron Gokaslan, Vanya Cohen, Ellie Pavlick, and Stefanie Tellex · 2019
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Decoupled weight decay regularization
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Fine-grain watermarking for intellectual property protection
Stefano Giovanni Rizzo, Flavio Bertini, and Danilo Montesi · 2019
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Defending against neural fake news
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 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
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Detecting cross-modal inconsistency to defend against neural fake news
Reuben Tan, Bryan Plummer, and Kate Saenko · 2020
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Neural text generation with unlikelihood training
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston · 2020
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Adversarial watermarking transformer: Towards tracing text provenance with data hiding
Sahar Abdelnabi and Mario Fritz · 2021
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Wikimedia downloads, 2022
Wikimedia Foundation · 2022
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Cater: Intellectual property protection on text generation apis via conditional watermarks
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Red teaming language models with language models
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Tracing text provenance via context-aware lexical substitution
Xi Yang, Jie Zhang, Kejiang Chen, Weiming Zhang, Zehua Ma, Feng Wang, and Nenghai Yu · 2022
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Distillation-resistant watermarking for model protection in NLP
OpenAI · 2023
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A robust semantics-based watermark for large language model against paraphrasing
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Can ai-generated text be reliably detected?
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Xuandong Zhao, Lei Li, and Yu-Xiang Wang · 2022
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Undetectable watermarks for language models
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Publicly detectable watermarking for language models
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Semstamp: A semantic watermark with paraphrastic robustness for text generation
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