Copyright Protection for Large Language Models: A Survey of Methods,
  Challenges, and Trends
Authors: name: Zhenhua Xu; name: Xubin Yue; name: Zhebo Wang; name: Qichen Liu; name: Xixiang Zhao; name: Jingxuan Zhang; name: Wenjun Zeng; name: Wengpeng Xing; name: Dezhang Kong; name: Changting Lin; name: Meng Han
Published: 2025-08-15 15:50:20

Abstract: 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.