Awesome-LLM-Watermark
UP-TO-DATE LLM Watermark paper. 🔥🔥🔥
Stars: 212
This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.
README:
This repo includes papers about the watermarking for text and images.
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Is Watermarking LLM-Generated Code Robust? Tiny ICLR 2024
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Tarun Suresh, Shubham Ugare, Gagandeep Singh, Sasa Misailovic
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Towards Better Statistical Understanding of Watermarking LLMs. Preprint.
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Zhongze Cai, Shang Liu, Hanzhao Wang, Huaiyang Zhong, Xiaocheng Li
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Topic-based Watermarks for LLM-Generated Text. Preprint.
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Alexander Nemecek, Yuzhou Jiang, Erman Ayday
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A Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules. Preprint.
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Xiang Li, Feng Ruan, Huiyuan Wang, Qi Long, Weijie J. Su
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WaterJudge: Quality-Detection Trade-off when Watermarking Large Language Models. Preprint.
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Piotr Molenda, Adian Liusie, Mark J. F. Gales
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Duwak: Dual Watermarks in Large Language Models. Preprint.
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Chaoyi Zhu, Jeroen Galjaard, Pin-Yu Chen, Lydia Y. Chen
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Lost in Overlap: Exploring Watermark Collision in LLMs. Preprint.
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Yiyang Luo, Ke Lin, Chao Gu
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WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off. Preprint.
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Eva Giboulot, Furon Teddy
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WARDEN: Multi-Directional Backdoor Watermarks for Embedding-as-a-Service Copyright Protection. Preprint.
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Anudeex Shetty, Yue Teng, Ke He, Qiongkai Xu
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EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models. Preprint.
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Ruisi Zhang, Farinaz Koushanfar
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Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models. Preprint.
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Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar, Pengtao Xie
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Attacking LLM Watermarks by Exploiting Their Strengths. Preprint.
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Qi Pang, Shengyuan Hu, Wenting Zheng, Virginia Smith
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Multi-Bit Distortion-Free Watermarking for Large Language Models. preprint.
- Massieh Kordi Boroujeny, Ya Jiang, Kai Zeng, Brian Mark
- https://arxiv.org/abs/2402.16578
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Watermarking Makes Language Models Radioactive. Preprint.
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Tom Sander, Pierre Fernandez, Alain Durmus, Matthijs Douze, Teddy Furon
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Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models. Preprint.
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Zhiwei He, Binglin Zhou, Hongkun Hao, Aiwei Liu, Xing Wang, Zhaopeng Tu, Zhuosheng Zhang, Rui Wang
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GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick. Preprint.
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Jiayi Fu, Xuandong Zhao, Ruihan Yang, Yuansen Zhang, Jiangjie Chen, Yanghua Xiao
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k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text. Preprint.
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Abe Bohan Hou, Jingyu Zhang, Yichen Wang, Daniel Khashabi, Tianxing He
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Proving membership in LLM pretraining data via data watermarks. Preprint.
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Johnny Tian-Zheng Wei, Ryan Yixiang Wang, Robin Jia
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Permute-and-Flip: An optimally robust and watermarkable decoder for LLMs. Preprint.
- Xuandong Zhao, Lei Li, Yu-Xiang Wang
- https://arxiv.org/abs/2402.05864
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Provably Robust Multi-bit Watermarking for AI-generated Text via Error Correction Code. Preprint.
- Wenjie Qu, Dong Yin, Zixin He, Wei Zou, Tianyang Tao, Jinyuan Jia, Jiaheng Zhang
- https://arxiv.org/abs/2401.16820
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Instructional Fingerprinting of Large Language Models. Preprint.
- Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen
- https://arxiv.org/abs/2401.12255
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Adaptive Text Watermark for Large Language Models. Preprint.
- Yepeng Liu, Yuheng Bu
- https://arxiv.org/abs/2401.13927
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Excuse me, sir? Your language model is leaking (information) Preprint.
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Or Zamir
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Cross-Attention Watermarking of Large Language Models. ICASSP2024.
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Folco Bertini Baldassini, Huy H. Nguyen, Ching-Chung Chang, Isao Echizen
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Optimizing watermarks for large language models. Preprint.
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Bram Wouters
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Towards Optimal Statistical Watermarking. Preprint.
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Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan
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A Survey of Text Watermarking in the Era of Large Language Models. Preprint. Survey paper.
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Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu
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On the Learnability of Watermarks for Language Models. Preprint.
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Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto
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New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking. Preprint.
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Karanpartap Singh, James Zou
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Mark My Words: Analyzing and Evaluating Language Model Watermarks. Preprint.
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Julien Piet, Chawin Sitawarin, Vivian Fang, Norman Mu, David Wagner
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I Know You Did Not Write That! A Sampling Based Watermarking Method for Identifying Machine Generated Text. Preprint.
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Kaan Efe Keleş, Ömer Kaan Gürbüz, Mucahid Kutlu
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Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring. Preprint
- Yuhang Li, Yihan Wang, Zhouxing Shi, Cho-Jui Hsieh
- https://arxiv.org/abs/2311.09668
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Performance Trade-offs of Watermarking Large Language Models. Preprint.
- Anirudh Ajith, Sameer Singh, Danish Pruthi
- https://arxiv.org/abs/2311.09816
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X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. Preprint.
- Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-fai Wong
- https://arxiv.org/abs/2311.09832
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WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models. ACL 2024.
- Shangqing Tu, Yuliang Sun, Yushi Bai, Jifan Yu, Lei Hou, Juanzi Li
- https://arxiv.org/abs/2311.07138
- Benchmark dataset
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Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models. Preprint.
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Hanlin Zhang, Benjamin L. Edelman, Danilo Francati, Daniele Venturi, Giuseppe Ateniese, Boaz Barak
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REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models. Preprint.
- Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara, Farinaz Koushanfar
- https://arxiv.org/abs/2310.12362
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Embarrassingly Simple Text Watermarks. Preprint.
- Ryoma Sato, Yuki Takezawa, Han Bao, Kenta Niwa, Makoto Yamada
- https://arxiv.org/abs/2310.08920
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Necessary and Sufficient Watermark for Large Language Models. Preprint.
- Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada
- https://arxiv.org/abs/2310.00833
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Functional Invariants to Watermark Large Transformers. Preprint.
- Fernandez Pierre, Couairon Guillaume, Furon Teddy, Douze Matthijs
- https://arxiv.org/abs/2310.11446
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Watermarking LLMs with Weight Quantization. EMNLP2023 findings.
- Linyang Li, Botian Jiang, Pengyu Wang, Ke Ren, Hang Yan, Xipeng Qiu
- https://arxiv.org/abs/2310.11237
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DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models. Preprint.
- Yihan Wu, Zhengmian Hu, Hongyang Zhang, Heng Huang
- https://arxiv.org/abs/2310.07710
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A Semantic Invariant Robust Watermark for Large Language Models. Preprint.
- Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen
- https://arxiv.org/abs/2310.06356
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SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation. Preprint.
- Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, Yulia Tsvetkov
- https://arxiv.org/abs/2310.03991
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Advancing Beyond Identification: Multi-bit Watermark for Language Models. Preprint.
- KiYoon Yoo, Wonhyuk Ahn, Nojun Kwak.
- https://arxiv.org/abs/2308.00221
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Three Bricks to Consolidate Watermarks for Large Language Models. Preprint.
- Pierre Fernandez, Antoine Chaffin, Karim Tit, Vivien Chappelier, Teddy Furon.
- https://arxiv.org/abs/2308.00113
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Towards Codable Text Watermarking for Large Language Models. Preprint.
- Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin, Fandong Meng, Jie Zhou, Xu Sun.
- https://arxiv.org/abs/2307.15992
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A Private Watermark for Large Language Models. Preprint.
- Aiwei Liu, Leyi Pan, Xuming Hu, Shu'ang Li, Lijie Wen, Irwin King, Philip S. Yu.
- https://arxiv.org/abs/2307.16230
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Robust Distortion-free Watermarks for Language Models. Preprint.
- Rohith Kuditipudi John Thickstun Tatsunori Hashimoto Percy Liang.
- https://arxiv.org/abs/2307.15593
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Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedy. Preprint.
- Yu Fu, Deyi Xiong, Yue Dong.
- https://arxiv.org/abs/2307.13808
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Provable Robust Watermarking for AI-Generated Text. Preprint.
- Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang.
- https://arxiv.org/abs/2306.17439
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On the Reliability of Watermarks for Large Language Models. Preprint.
- John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein.
- https://arxiv.org/abs/2306.04634
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Undetectable Watermarks for Language Models. Preprint.
- Miranda Christ, Sam Gunn, Or Zamir.
- https://arxiv.org/abs/2306.09194
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Watermarking Text Data on Large Language Models for Dataset Copyright Protection. Preprint.
- Yixin Liu, Hongsheng Hu, Xuyun Zhang, Lichao Sun.
- https://arxiv.org/abs/2305.13257
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Baselines for Identifying Watermarked Large Language Models. Preprint.
- Leonard Tang, Gavin Uberti, Tom Shlomi.
- https://arxiv.org/abs/2305.18456
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Who Wrote this Code? Watermarking for Code Generation. Preprint.
- Taehyun Lee, Seokhee Hong, Jaewoo Ahn, Ilgee Hong, Hwaran Lee, Sangdoo Yun, Jamin Shin, Gunhee Kim.
- https://arxiv.org/abs/2305.15060
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Robust Multi-bit Natural Language Watermarking through Invariant Features. ACL 2023.
- KiYoon Yoo, Wonhyuk Ahn, Jiho Jang, Nojun Kwak.
- https://arxiv.org/abs/2305.01904
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Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark. ACL 2023.
- Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie.
- https://arxiv.org/abs/2305.10036
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Watermarking Text Generated by Black-Box Language Models. Preprint.
- Xi Yang, Kejiang Chen, Weiming Zhang, Chang Liu, Yuang Qi, Jie Zhang, Han Fang, Nenghai Yu.
- https://arxiv.org/abs/2305.08883
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Protecting Language Generation Models via Invisible Watermarking. ICML 2023.
- Xuandong Zhao, Yu-Xiang Wang, Lei Li.
- https://arxiv.org/abs/2302.03162
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A Watermark for Large Language Models. ICML 2023. Outstanding Paper Award
- John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein.
- https://arxiv.org/abs/2301.10226
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Distillation-Resistant Watermarking for Model Protection in NLP. EMNLP 2022
- Xuandong Zhao, Lei Li, Yu-Xiang Wang.
- https://arxiv.org/abs/2210.03312
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CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. NeurIPS 2022
- Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia.
- https://arxiv.org/abs/2209.08773
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Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding. IEEE S&P 2021
- Sahar Abdelnabi, Mario Fritz.
- https://arxiv.org/abs/2009.03015
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Watermarking GPT Outputs. slides 2023
- Scott Aaronson, Hendrik Kirchner
- https://www.scottaaronson.com/talks/watermark.ppt
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Watermarking the Outputs of Structured Prediction with an Application in Statistical Machine Translation. EMNLP 2011
- Ashish Venugopal, Jakob Uszkoreit, David Talbot, Franz Och, Juri Ganitkevitch.
- https://aclanthology.org/D11-1126/
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Flexible and Secure Watermarking for Latent Diffusion Model. MM23.
- Cheng Xiong, Chuan Qin, Guorui Feng, Xinpeng Zhang
- https://dl.acm.org/doi/abs/10.1145/3581783.3612448
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Leveraging Optimization for Adaptive Attacks on Image Watermarks. Preprint.
- Nils Lukas, Abdulrahman Diaa, Lucas Fenaux, Florian Kerschbaum
- https://arxiv.org/abs/2309.16952
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Catch You Everything Everywhere: Guarding Textual Inversion via Concept Watermarking. Preprint.
- Weitao Feng, Jiyan He, Jie Zhang, Tianwei Zhang, Wenbo Zhou, Weiming Zhang, Nenghai Yu
- https://arxiv.org/abs/2309.05940
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Hey That's Mine Imperceptible Watermarks are Preserved in Diffusion Generated Outputs. Preprint.
- Luke Ditria, Tom Drummond
- https://arxiv.org/abs/2308.11123
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Generative Watermarking Against Unauthorized Subject-Driven Image Synthesis. Preprint.
- Yihan Ma, Zhengyu Zhao, Xinlei He, Zheng Li, Michael Backes, Yang Zhang
- https://arxiv.org/abs/2306.07754
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Invisible Image Watermarks Are Provably Removable Using Generative AI. Preprint.
- Xuandong Zhao, Kexun Zhang, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei Li.
- https://arxiv.org/abs/2306.01953
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Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust. Preprint.
- Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein.
- https://arxiv.org/abs/2305.20030
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Evading Watermark based Detection of AI-Generated Content. CCS 2023.
- Zhengyuan Jiang, Jinghuai Zhang, Neil Zhenqiang Gong.
- https://arxiv.org/abs/2305.03807
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The Stable Signature: Rooting Watermarks in Latent Diffusion Models. ICCV 2023.
- Pierre Fernandez, Guillaume Couairon, Hervé Jégou, Matthijs Douze, Teddy Furon.
- https://arxiv.org/abs/2303.15435
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Watermarking Images in Self-Supervised Latent Spaces. ICASSP 2022.
- Pierre Fernandez, Alexandre Sablayrolles, Teddy Furon, Hervé Jégou, Matthijs Douze.
- https://arxiv.org/abs/2112.09581
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The GraphRAG project is a data pipeline and transformation suite designed to extract meaningful, structured data from unstructured text using LLMs. It enhances LLMs' ability to reason about private data. The repository provides guidance on using knowledge graph memory structures to enhance LLM outputs, with a warning about the potential costs of GraphRAG indexing. It offers contribution guidelines, development resources, and encourages prompt tuning for optimal results. The Responsible AI FAQ addresses GraphRAG's capabilities, intended uses, evaluation metrics, limitations, and operational factors for effective and responsible use.
langtest
LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.
Awesome-Jailbreak-on-LLMs
Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.