mlsanityData to 14 Oct 2026

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends

arXiv 2508.11548 ↗First posted 15 Aug 2025cs.CRcited by 20

On the map: LLM safety and security → Watermarking generated content and models

Abstract (arXiv)

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.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Placed in Watermarking generated content and models, one of 12 directions in LLM safety and security. Builds on 100 of its 182 references that are in the map. First posted on arXiv 15 Aug 2025.

Builds on

100 of 182 references.

Closest ancestors · 25

Same direction, newest first

  1. 2025Invariant-based Robust Weights Watermark for Large Language Models11 Jul
  2. 2025MEraser: An Effective Fingerprint Erasure Approach for Large Language Models14 Jun
  3. 2025Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness9 Jun
  4. 2025Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking6 Mar
  5. 2025Robust Data Watermarking in Language Models by Injecting Fictitious Knowledge6 Mar
  6. 2024Watermarking Language Models through Language Models7 Nov
  7. 2024NSmark: Null Space Based Black-box Watermarking Defense Framework for Language Models16 Oct
  8. 2024Signal Watermark on Large Language Models9 Oct
  9. 2024Fingerprint Vector: Enabling Scalable and Efficient Model Fingerprint Transfer via Vector Addition13 Sep
  10. 2024Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing11 Apr
  11. 2024Have You Merged My Model? On The Robustness of Large Language Model IP Protection Methods Against Model Merging8 Apr
  12. 2024Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning22 Feb
13 more
  1. 2024Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models21 Feb
  2. 2024k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text17 Feb
  3. 2023On the Learnability of Watermarks for Language Models7 Dec
  4. 2023Turning Your Strength into Watermark: Watermarking Large Language Model via Knowledge Injection16 Nov
  5. 2023A Robust Semantics-based Watermark for Large Language Model against Paraphrasing15 Nov
  6. 2023REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models18 Oct
  7. 2023Embarrassingly Simple Text Watermarks13 Oct
  8. 2023Robust Distortion-free Watermarks for Language Models28 Jul
  9. 2023Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedy25 Jul
  10. 2023Who Wrote this Code? Watermarking for Code Generation24 May
  11. 2023Robust Multi-bit Natural Language Watermarking through Invariant Features3 May
  12. 2023Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks22 Apr
  13. 2022Watermarking Pre-trained Language Models with Backdooring14 Oct

Other references · 75

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2023GPT-4 Technical Reportcited by 18,396
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  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  6. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
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38 more
  1. 2016Categorical Reparameterization with Gumbel-Softmaxcited by 2,739
  2. 2020Extracting Training Data from Large Language Modelscited by 2,189
  3. 2019BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questionscited by 2,183
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  11. 2018WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representationscited by 372
  12. 2018Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooringcited by 357
  13. 2025Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learningcited by 262
  14. 2017Embedding Watermarks into Deep Neural Networkscited by 248
  15. 2023Automatically Auditing Large Language Models via Discrete Optimizationcited by 191
  16. 2023Is ChatGPT A Good Translator? Yes With GPT-4 As The Enginecited by 176
  17. 2020Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hidingcited by 130
  18. 2024On Memorization of Large Language Models in Logical Reasoningcited by 117
  19. 2022Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protectioncited by 86
  20. 2019IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundarycited by 70
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  25. 2020A Systematic Review on Model Watermarking for Neural Networkscited by 52
  26. 2024Hey, That's My Model! Introducing Chain & Hash, An LLM Fingerprinting Techniquecited by 37
  27. 2024TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identificationcited by 36
  28. 2024REEF: Representation Encoding Fingerprints for Large Language Modelscited by 36
  29. 2024Chain-of-Scrutiny: Detecting Backdoor Attacks for Large Language Modelscited by 28
  30. 2024A Fingerprint for Large Language Modelscited by 28
  31. 2023WatME: Towards Lossless Watermarking Through Lexical Redundancycited by 27
  32. 2024Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillationcited by 27
  33. 2024Here's a Free Lunch: Sanitizing Backdoored Models with Model Mergecited by 26
  34. 2024A Survey on the Honesty of Large Language Modelscited by 23
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  37. 2024PhyloLM : Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarkscited by 19
  38. 2025CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Qualitycited by 19

50 most cited of 75 All 75 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 8; 2026: 12.

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  1. 2025SoK: Large Language Model Copyright Auditing via Fingerprintingcited by 15
  2. 2025LLM DNA: Tracing Model Evolution via Functional Representationscited by 15
  3. 2025VideoEraser: Concept Erasure in Text-to-Video Diffusion Modelscited by 14
  4. 2026AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playingcited by 9
  5. 2025Are Robust LLM Fingerprints Adversarially Robust?cited by 8
  6. 2025Every Language Model Has a Forgery-Resistant Signaturecited by 4
  7. 2026ICPO: Illocution-Calibrated Policy Optimization for Multi-Turn Conversationcited by 2
  8. 2026P2S: Probabilistic Process Supervision for General-Domain Reasoning Question Answeringcited by 2
  9. 2026RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resiliencecited by 2
  10. 2025Spectral Logit Sculpting: Adaptive Low-Rank Logit Transformation for Controlled Text Generationcited by 1
  11. 2026ForgetMark: Stealthy Fingerprint Embedding via Targeted Unlearning in Language Modelscited by 1
  12. 2026Provable Model Provenance Set for Large Language Modelscited by 1
8 more
  1. 2026Implicit Identity Technologies for LLMs: Fingerprinting and Watermarking across Datasets, Models, and Generated Contentcited by 1
  2. 2026Agentic Evaluation of Copyright Law Compliancecited by 1
  3. 2025CIDER: A Causal Cure for Brand-Obsessed Text-to-Image Modelscited by 0
  4. 2025MarkTune: Improving the Quality-Detectability Trade-off in Open-Weight LLM Watermarkingcited by 0
  5. 2026DNF: Dual-Layer Nested Fingerprinting for Large Language Model Intellectual Property Protectioncited by 0
  6. 2026FNF: Functional Network Fingerprint for Large Language Modelscited by 0
  7. 2026Verify Claimed Text-to-Image Models via Boundary-Aware Prompt Optimizationcited by 0
  8. 2026Beyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoodscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?
  2. 2024Watermarking Large Language Models and the Generated Content: Opportunities and Challenges
  3. 2025PRO: Enabling Precise and Robust Text Watermark for Open-Source LLMs
  4. 2025SoK: Are Watermarks in LLMs Ready for Deployment?
  5. 2024From Intentions to Techniques: A Comprehensive Taxonomy and Challenges in Text Watermarking for Large Language Models
  6. 2023A Survey of Text Watermarking in the Era of Large Language Models
  7. 2025Watermarking Large Language Models in Europe: Interpreting the AI Act in Light of Technology
  8. 2025DERMARK: A Dynamic, Efficient and Robust Multi-bit Watermark for Large Language Models