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The widely adopted and powerful generative large language models (LLMs) have raised concerns about intellectual property rights violations and the spread of machine-generated misinformation. Watermarking serves as a promising approch to…

Cryptography and Security · Computer Science 2024-10-28 Ruisi Zhang , Farinaz Koushanfar

To mitigate the potential harms of Large Language Models (LLMs)generated text, researchers have proposed watermarking, a process of embedding detectable signals within text. With watermarking, we can always accurately detect LLM-generated…

Computation and Language · Computer Science 2025-11-19 William Guo , Adaku Uchendu , Ana Smith

Large Language Models (LLMs) have experienced rapid advancements, with applications spanning a wide range of fields, including sentiment classification, review generation, and question answering. Due to their efficiency and versatility,…

Cryptography and Security · Computer Science 2025-06-17 Yugeng Liu , Tianshuo Cong , Michael Backes , Zheng Li , Yang Zhang

With the rapid advancement and extensive application of artificial intelligence technology, large language models (LLMs) are extensively used to enhance production, creativity, learning, and work efficiency across various domains. However,…

Cryptography and Security · Computer Science 2024-09-04 Yuqing Liang , Jiancheng Xiao , Wensheng Gan , Philip S. Yu

The recent advancements in large language models (LLMs) have sparked a growing apprehension regarding the potential misuse. One approach to mitigating this risk is to incorporate watermarking techniques into LLMs, allowing for the tracking…

Cryptography and Security · Computer Science 2023-10-19 Zhengmian Hu , Lichang Chen , Xidong Wu , Yihan Wu , Hongyang Zhang , Heng Huang

Text watermarking algorithms are crucial for protecting the copyright of textual content. Historically, their capabilities and application scenarios were limited. However, recent advancements in large language models (LLMs) have…

Computation and Language · Computer Science 2024-08-12 Aiwei Liu , Leyi Pan , Yijian Lu , Jingjing Li , Xuming Hu , Xi Zhang , Lijie Wen , Irwin King , Hui Xiong , Philip S. Yu

Detecting whether copyright holders' works were used in LLM pretraining is poised to be an important problem. This work proposes using data watermarks to enable principled detection with only black-box model access, provided that the…

Cryptography and Security · Computer Science 2024-08-20 Johnny Tian-Zheng Wei , Ryan Yixiang Wang , Robin Jia

Large Language Models (LLMs) excel in various applications, including text generation and complex tasks. However, the misuse of LLMs raises concerns about the authenticity and ethical implications of the content they produce, such as…

Cryptography and Security · Computer Science 2024-12-02 Zesen Liu , Tianshuo Cong , Xinlei He , Qi Li

Data watermarking in language models injects traceable signals, such as specific token sequences or stylistic patterns, into copyrighted text, allowing copyright holders to track and verify training data ownership. Previous data…

Cryptography and Security · Computer Science 2025-07-29 Xinyue Cui , Johnny Tian-Zheng Wei , Swabha Swayamdipta , Robin Jia

With the rapid growth of Large Language Models (LLMs), safeguarding textual content against unauthorized use is crucial. Watermarking offers a vital solution, protecting both - LLM-generated and plain text sources. This paper presents a…

Computation and Language · Computer Science 2025-07-08 Harsh Nishant Lalai , Aashish Anantha Ramakrishnan , Raj Sanjay Shah , Dongwon Lee

The indistinguishability of large language model (LLM) output from human-authored content poses significant challenges, raising concerns about potential misuse of AI-generated text and its influence on future model training. Watermarking…

Cryptography and Security · Computer Science 2026-04-16 Alexander Nemecek , Yuzhou Jiang , Erman Ayday

Large language models (LLMs) have demonstrated outstanding performance, making them valuable digital assets with significant commercial potential. Unfortunately, the LLM and its API are susceptible to intellectual property theft.…

Cryptography and Security · Computer Science 2024-07-25 Shuai Li , Kejiang Chen , Kunsheng Tang , Jie Zhang , Weiming Zhang , Nenghai Yu , Kai Zeng

Large Language Models (LLMs) have demonstrated remarkable capabilities of generating texts resembling human language. However, they can be misused by criminals to create deceptive content, such as fake news and phishing emails, which raises…

Cryptography and Security · Computer Science 2025-01-29 Wenjie Qu , Wengrui Zheng , Tianyang Tao , Dong Yin , Yanze Jiang , Zhihua Tian , Wei Zou , Jinyuan Jia , Jiaheng Zhang

Large Language Models (LLMs) have transformed natural language processing, demonstrating impressive capabilities across diverse tasks. However, deploying these models introduces critical risks related to intellectual property violations and…

Cryptography and Security · Computer Science 2025-12-24 Kieu Dang , Phung Lai , NhatHai Phan , Yelong Shen , Ruoming Jin , Abdallah Khreishah , My T. Thai

Recent advancements in Large Language Models (LLMs) raised concerns over potential misuse, such as for spreading misinformation. In response two counter measures emerged: machine learning-based detectors that predict if text is synthetic,…

Machine Learning · Computer Science 2025-04-17 David Khachaturov , Robert Mullins , Ilia Shumailov , Sumanth Dathathri

The rapid advancement of customized Large Language Models (LLMs) offers considerable convenience. However, it also intensifies concerns regarding the protection of copyright/confidential information. With the extensive adoption of private…

Cryptography and Security · Computer Science 2024-12-18 Yuehan Zhang , Peizhuo Lv , Yinpeng Liu , Yongqiang Ma , Wei Lu , Xiaofeng Wang , Xiaozhong Liu , Jiawei Liu

Copyright protection for large language models is of critical importance, given their substantial development costs, proprietary value, and potential for misuse. Existing surveys have predominantly focused on techniques for tracing…

Cryptography and Security · Computer Science 2026-04-08 Zhenhua Xu , Xubin Yue , Zhebo Wang , Haobo Zhang , Qichen Liu , Xixiang Zhao , Jingxuan Zhang , Wenjun Zeng , Wengpeng Xing , Dezhang Kong , Changting Lin , Meng Han

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. The LLM watermark scheme commonly includes…

Cryptography and Security · Computer Science 2024-05-31 Zhaoxi Zhang , Xiaomei Zhang , Yanjun Zhang , Leo Yu Zhang , Chao Chen , Shengshan Hu , Asif Gill , Shirui Pan

Large Language Models (LLMs) have demonstrated remarkable capabilities, but their training requires extensive data and computational resources, rendering them valuable digital assets. Therefore, it is essential to watermark LLMs to protect…

Cryptography and Security · Computer Science 2025-10-21 Shuai Li , Kejiang Chen , Jun Jiang , Jie Zhang , Qiyi Yao , Kai Zeng , Weiming Zhang , Nenghai Yu

The rapid advancement of large language models (LLMs) has raised concerns regarding their potential misuse, particularly in generating fake news and misinformation. To address these risks, watermarking techniques for autoregressive language…

Cryptography and Security · Computer Science 2025-06-24 Koichi Nagatsuka , Terufumi Morishita , Yasuhiro Sogawa
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