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Watermarking has emerged as a prominent technique for LLM-generated content detection by embedding imperceptible patterns.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 1904
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Individual choice behavior: A theoretical analysis
Gerard Debreu. 1960 · 1960
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The meaning and use of the area under a receiver operating characteristic (roc) curve
James A Hanley and Barbara J McNeil. 1982 · 1982
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Nonlinear Programming
D.P. Bertsekas. 1999 · 1999
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Loess:: a nonparametric, graphical tool for depicting relationships between variables
William G. Jacoby. 2000 · 2000
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
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Sequence-level knowledge distillation
Yoon Kim and Alexander M. Rush. 2016 · 2016
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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. 2020 · 2020
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On the dangers of stochastic parrots: Can language models be too big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Paraphrastic representations at scale
John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-kirkpatrick. 2022 · 2022
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Watermarking of large language models
Scott Aaronson. 2023 · 2023
Earlier work this paper cites.
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy
Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, and Kam-fai Wong. 2023 · 2023
Cited alongside, same era.
Three Bricks to Consolidate Watermarks for Large Language Models
Pierre Fernandez, Antoine Chaffin, Karim Tit, Vivien Chappelier, and Teddy Furon. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Unbiased Watermark for Large Language Models
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, and Heng Huang. 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
Later among the works it cites.
Towards Codable Text Watermarking for Large Language Models
Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin, Fandong Meng, Jie Zhou, and Xu Sun. 2023 · 2023
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A Survey on Detection of LLMs-Generated Content
Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda Petzold, William Yang Wang, and Wei Cheng. 2023 · 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
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Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, and Mohit Iyyer. 2023 · 2023
Cited alongside, same era.
Robust Distortion-free Watermarks for Language Models
Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, and Percy Liang. 2023 · 2023
Cited alongside, same era.
Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring
Yuhang Li, Yihan Wang, Zhouxing Shi, and Cho-Jui Hsieh. 2023 · 2023
Cited alongside, same era.
Detectgpt: Zero-shot machine-generated text detection using probability curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, and Chelsea Finn. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
On the zero-shot generalization of machine-generated text detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, and Tianxing He. 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.
A Watermark for Large Language Models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023a
Cited in the paper.
Xuandong Zhao, Prabhanjan Ananth, Lei Li, and Yu-Xiang Wang. 2023 · 2023
Later among the works it cites.
On the learnability of watermarks for language models
Chenchen Gu, Xiang Lisa Li, Percy Liang, and Tatsunori Hashimoto. 2024 · 2024
Closest in time.
Watermark Stealing in Large Language Models
Nikola Jovanović, Robin Staab, and Martin Vechev. 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.
An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, Guanting Dong, Haoran Wei, Huan Lin, Jialong Tang, Jialin Wang, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Ma, Jianxin Yang, Jin Xu, Jingren Zhou, Jinze Bai, Jinzheng He, Junyang Lin, Kai Dang, Keming Lu, Keqin Chen, Kexin Yang, Mei Li, Mingfeng Xue, Na Ni, Pei Zhang, Peng Wang, Ru Peng, Rui Men, Ruize Gao, Runji Lin, Shijie Wang, Shuai Bai, Sinan Tan, Tianhang Zhu, Tianhao Li, Tianyu Liu, Wenbin Ge, Xiaodong Deng, Xiaohuan Zhou, Xingzhang Ren, Xinyu Zhang, Xipin Wei, Xuancheng Ren, Xuejing Liu, Yang Fan, Yang Yao, Yichang Zhang, Yu Wan, Yunfei Chu, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, Zhifang Guo, and Zhihao Fan. 2024 · 2024
Closest in time.
Large Language Model Watermark Stealing With Mixed Integer Programming
Zhaoxi Zhang, Xiaomei Zhang, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shengshan Hu, Asif Gill, and Shirui Pan. 2024 · 2024
Closest in time.