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The Large Language Model (LLM) watermark is a newly emerging technique that shows promise in addressing concerns surrounding LLM copyright, monitoring AI-generated text, and preventing its misuse.
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 · 1901
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910
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The hiding virtues of ambiguity: quantifiably resilient watermarking of natural language text through synonym substitutions. In Proceedings of the 8th workshop on Multimedia and security . 164–174
Umut Topkara, Mercan Topkara, and Mikhail J Atallah. 2006 · 2006
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Categorical Reparameterization with Gumbel-Softmax. In International Conference on Learning Representations
Eric Jang, Shixiang Gu, and Ben Poole. 2017 · 2017
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 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 · 2019
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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
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Publicly Detectable Watermarking for Language Models
Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, and Mingyuan Wang. 2023 · 2023
Earlier work this paper cites.
Gurobi Optimizer Reference Manual
Gurobi Optimization, LLC. 2023 · 2023
Earlier work this paper cites.
Large language models can be used to effectively scale spear phishing campaigns
Julian Hazell. 2023 · 2023
Earlier work this paper cites.
Semstamp: A semantic watermark with paraphrastic robustness for text generation
Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, and Yulia Tsvetkov. 2023 · 2023
Earlier work this paper cites.
Evading Watermark based Detection of AI-Generated Content
Zhengyuan Jiang, Jinghuai Zhang, and Neil Zhenqiang Gong. 2023 · 2023
Cited alongside, same era.
ChatGPT for good? On opportunities and challenges of large language models for education
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, et al · 2023
Cited alongside, same era.
A watermark for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023 · 2023
Cited alongside, same era.
Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense. In NeuraIPS
Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, and Mohit Iyyer. 2023 · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Later among the works it cites.
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Hanlin Zhang, Benjamin L. Edelman, Danilo Francati, Daniele Venturi, Giuseppe Ateniese, and Boaz Barak. 2023 · 2023
Later among the works it cites.
Zhiwei He, Binglin Zhou, Hongkun Hao, Aiwei Liu, Xing Wang, Zhaopeng Tu, Zhuosheng Zhang, and Rui Wang. 2024 · 2024
Closest in time.
Watermark Stealing in Large Language Models
Nikola Jovanović, Robin Staab, and Martin Vechev. 2024 · 2024
Closest in time.
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Taehyun Lee, Seokhee Hong, Jaewoo Ahn, Ilgee Hong, Hwaran Lee, Sangdoo Yun, Jamin Shin, and Gunhee Kim. 2023 · 2023
Cited alongside, same era.
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature. In International Conference on Machine Learning
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, and Chelsea Finn. 2023 · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, and Jiliang Tang. 2023 · 2023
Cited alongside, same era.
Can ai-generated text be reliably detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi. 2023 · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Cited alongside, same era.
On the Reliability of Watermarks for Large Language Models. In The Twelfth International Conference on Learning Representations
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, and Tom Goldstein. 2024 · 2024
Closest in time.
A Semantic Invariant Robust Watermark for Large Language Models. In The Twelfth International Conference on Learning Representations
Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, and Lijie Wen. 2024 · 2024
Closest in time.
Attacking LLM Watermarks by Exploiting Their Strengths
Qi Pang, Shengyuan Hu, Wenting Zheng, and Virginia Smith. 2024 · 2024
Closest in time.
Bypassing LLM Watermarks with Color-Aware Substitutions
Qilong Wu and Varun Chandrasekaran. 2024 · 2024
Closest in time.
Detecting AI-Generated Code Assignments Using Perplexity of Large Language Models
Zhenyu Xu and Victor S. Sheng. 2024 · 2024
Closest in time.
Provable Robust Watermarking for AI-Generated Text. In The Twelfth International Conference on Learning Representations
Xuandong Zhao, Prabhanjan Vijendra Ananth, Lei Li, and Yu-Xiang Wang. 2024 · 2024
Closest in time.