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 LLM-generated content-namely, text watermarking-while a systematic exploration of methods for protecting the models themselves (i.e., model watermarking and model fingerprinting) remains absent. Moreover, the relationships and distinctions among text watermarking, model watermarking, and model fingerprinting have not been comprehensively clarified. This work presents a comprehensive survey of the current state of LLM copyright protection technologies, with a focus on model fingerprinting, covering the following aspects: (1) clarifying the conceptual connection from text watermarking to model watermarking and fingerprinting, and adopting a unified terminology that incorporates model watermarking into the broader fingerprinting framework; (2) providing an overview and comparison of diverse text watermarking techniques, highlighting cases where such methods can function as model fingerprinting; (3) systematically categorizing and comparing existing model fingerprinting approaches for LLM copyright protection; (4) presenting, for the first time, techniques for fingerprint transfer and fingerprint removal; (5) summarizing evaluation metrics for model fingerprints, including effectiveness, harmlessness, robustness, stealthiness, and reliability; and (6) discussing open challenges and future research directions. This survey aims to offer researchers a thorough understanding of both text watermarking and model fingerprinting technologies in the era of LLMs, thereby fostering further advances in protecting their intellectual property.

翻译：大语言模型的版权保护至关重要，原因在于其高昂的开发成本、专有价值及潜在的滥用风险。现有综述主要聚焦于追踪模型生成内容的技术（即文本水印），但对保护模型本身的方法（即模型水印与模型指纹）的系统性探讨仍付之阙如。此外，文本水印、模型水印与模型指纹之间的关系与区别尚未得到全面厘清。本文对当前大语言模型版权保护技术的现状进行了全面综述，重点关注模型指纹，涵盖以下方面：（1）厘清从文本水印到模型水印及指纹的概念联系，并采用将模型水印纳入更广泛指纹框架的统一术语体系；（2）概述并比较多种文本水印技术，突出其中可作为模型指纹方法的情形；（3）系统分类与比较现有面向大语言模型版权保护的模型指纹方法；（4）首次提出指纹迁移与指纹移除技术；（5）总结模型指纹的评价指标，包括有效性、无害性、鲁棒性、隐蔽性和可靠性；（6）探讨开放挑战与未来研究方向。本综述旨在帮助研究人员深入理解大语言模型时代下的文本水印与模型指纹技术，从而推动其知识产权保护领域的进一步发展。