Embarrassingly Simple Text Watermarks
On the map: LLM safety and security → Watermarking generated content and models
Abstract (arXiv)
We propose Easymark, a family of embarrassingly simple yet effective watermarks. Text watermarking is becoming increasingly important with the advent of Large Language Models (LLM). LLMs can generate texts that cannot be distinguished from human-written texts. This is a serious problem for the credibility of the text. Easymark is a simple yet effective solution to this problem. Easymark can inject a watermark without changing the meaning of the text at all while a validator can detect if a text was generated from a system that adopted Easymark or not with high credibility. Easymark is extremely easy to implement so that it only requires a few lines of code. Easymark does not require access to LLMs, so it can be implemented on the user-side when the LLM providers do not offer watermarked LLMs. In spite of its simplicity, it achieves higher detection accuracy and BLEU scores than the state-of-the-art text watermarking methods. We also prove the impossibility theorem of perfect watermarking, which is valuable in its own right. This theorem shows that no matter how sophisticated a watermark is, a malicious user could remove it from the text, which motivate us to use a simple watermark such as Easymark. We carry out experiments with LLM-generated texts and confirm that Easymark can be detected reliably without any degradation of BLEU and perplexity, and outperform state-of-the-art watermarks in terms of both quality and reliability.
Key facts. Cited by 29 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 36 of its 44 references that are in the map. First posted on arXiv 13 Oct 2023.
Builds on
36 of 44 references.
Closest ancestors · 13
Same direction, newest first
- 2023Necessary and Sufficient Watermark for Large Language Models2 Oct
- 2023Provable Robust Watermarking for AI-Generated Text30 Jun
- 2023On the Reliability of Watermarks for Large Language Models7 Jun
- 2023Undetectable Watermarks for Language Models25 May
- 2023Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark17 May
- 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense23 Mar
- 2023Can AI-Generated Text be Reliably Detected?17 Mar
- 2023Protecting Language Generation Models via Invisible Watermarking6 Feb
- 2023A Watermark for Large Language Models24 Jan
- 2022Watermarking Pre-trained Language Models with Backdooring14 Oct
- 2022CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks19 Sep
- 2022The Ethical Need for Watermarks in Machine-Generated Language7 Sep
Other references · 23
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2023GPT-4 Technical Reportcited by 18,396
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
- 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
- 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,312
- 2023DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvaturecited by 726
- 2019GLTR: Statistical Detection and Visualization of Generated Textcited by 496
- 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 481
- 2021All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Textcited by 287
- 2020Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hidingcited by 130
11 more
- 2022Human heuristics for AI-generated language are flawedcited by 105
- 2023Regulating ChatGPT and other Large Generative AI Modelscited by 104
- 2019Neural Linguistic Steganographycited by 78
- 2019The Limitations of Stylometry for Detecting Machine-Generated Fake Newscited by 63
- 2017Generating Steganographic Text with LSTMscited by 44
- 2019Towards Near-imperceptible Steganographic Textcited by 32
- 2021Frustratingly Easy Edit-based Linguistic Steganography with a Masked Language Modelcited by 30
- 2021Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data?cited by 7
- 2022Towards Principled User-side Recommender Systemscited by 7
- 2021Retrieving Black-box Optimal Images from External Databasescited by 6
- 2022CLEAR: A Fully User-side Image Search Systemcited by 6
Built on by
Citing papers per year: 2023: 3; 2024: 11; 2025: 11; 2026: 4.
29 papers.
Sort:
By area:
- 2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Modelscited by 87
- 2024Adaptive Text Watermark for Large Language Modelscited by 67
- 2024SoK: Watermarking for AI-Generated Contentcited by 51
- 2024Copyright Protection in Generative AI: A Technical Perspectivecited by 38
- 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Surveycited by 30
- 2023Towards Optimal Statistical Watermarkingcited by 26
- 2024Watermarking Techniques for Large Language Models: A Surveycited by 23
- 2024Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approachcited by 22
- 2025Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trendscited by 20
- 2024Can Watermarked LLMs be Identified by Users via Crafted Prompts?cited by 13
- 2025Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learningcited by 10
- 2025In-Context Watermarks for Large Language Modelscited by 10
17 more
- 2024Topic-Based Watermarks for Large Language Modelscited by 8
- 2024Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Modelscited by 8
- 2025Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoptioncited by 7
- 2023Making Translators Privacy-aware on the User's Sidecited by 3
- 2024User-Side Realizationcited by 3
- 2024A Certified Robust Watermark For Large Language Modelscited by 3
- 2025BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarkscited by 3
- 2024Overhead-free User-side Recommender Systemscited by 2
- 2025Learning to Watermark: A Selective Watermarking Framework for Large Language Models via Multi-Objective Optimizationcited by 1
- 2025Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codescited by 1
- 2026LLM Watermarking as Big Data Provenance: A Deployment-Oriented Systematizationcited by 1
- 2025WaterDrum: Watermarking for Data-centric Unlearning Metriccited by 0
- 2025PRIVMARK: Private Large Language Models Watermarking with MPCcited by 0
- 2025Watermarking Large Language Models in Europe: Interpreting the AI Act in Light of Technologycited by 0
- 2026Preserving Structure, Strengthening Signals: A Grammar-Driven Approach to Optimize the Trade-off Between Quality and Detectability in Code Watermarkingcited by 0
- 2026AgentRecommender: LLM Agents Enable Customizable Recommender Systems on the User Sidecited by 0
- 2026ByteMark: A Unified Byte-Level Watermark for Detection Across Language Modelscited by 0
- 2026ByteMark: A Unified Byte-Level Watermark for Detection Across Language Models10 Oct 2026
- 2026AgentRecommender: LLM Agents Enable Customizable Recommender Systems on the User Side25 Sep 2026
- 2026Preserving Structure, Strengthening Signals: A Grammar-Driven Approach to Optimize the Trade-off Between Quality and Detectability in Code Watermarking11 Jul 2026
- 2026LLM Watermarking as Big Data Provenance: A Deployment-Oriented Systematization11 Jul 2026
- 2025Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codes19 Dec 2025
- 2025Watermarking Large Language Models in Europe: Interpreting the AI Act in Light of Technology5 Nov 2025
- 2025Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption21 Oct 2025
- 2025Learning to Watermark: A Selective Watermarking Framework for Large Language Models via Multi-Objective Optimization13 Oct 2025
- 2025PRIVMARK: Private Large Language Models Watermarking with MPC29 Sep 2025
- 2025Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends15 Aug 2025
- 2025In-Context Watermarks for Large Language Models22 May 2025
- 2025WaterDrum: Watermarking for Data-centric Unlearning Metric8 May 2025
17 more
- 2025Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learning9 Apr 2025
- 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey8 Feb 2025
- 2025BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks21 Jan 2025
- 2024SoK: Watermarking for AI-Generated Content27 Nov 2024
- 2024Overhead-free User-side Recommender Systems12 Nov 2024
- 2024Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models27 Oct 2024
- 2024Can Watermarked LLMs be Identified by Users via Crafted Prompts?4 Oct 2024
- 2024Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach3 Oct 2024
- 2024A Certified Robust Watermark For Large Language Models29 Sep 2024
- 2024Watermarking Techniques for Large Language Models: A Survey26 Aug 2024
- 2024Topic-Based Watermarks for Large Language Models2 Apr 2024
- 2024User-Side Realization23 Mar 2024
- 2024Copyright Protection in Generative AI: A Technical Perspective4 Feb 2024
- 2024Adaptive Text Watermark for Large Language Models25 Jan 2024
- 2023Towards Optimal Statistical Watermarking13 Dec 2023
- 2023Making Translators Privacy-aware on the User's Side7 Dec 2023
- 2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models7 Nov 2023
- 2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Modelscited by 87
- 2024Adaptive Text Watermark for Large Language Modelscited by 67
- 2024SoK: Watermarking for AI-Generated Contentcited by 51
- 2023Towards Optimal Statistical Watermarkingcited by 26
- 2024Watermarking Techniques for Large Language Models: A Surveycited by 23
- 2024Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approachcited by 22
- 2025Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trendscited by 20
- 2024Can Watermarked LLMs be Identified by Users via Crafted Prompts?cited by 13
- 2025Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learningcited by 10
- 2025In-Context Watermarks for Large Language Modelscited by 10
- 2024Topic-Based Watermarks for Large Language Modelscited by 8
- 2025Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoptioncited by 7
12 most cited of 20 All 20 (JSON)
- 2026ByteMark: A Unified Byte-Level Watermark for Detection Across Language Models10 Oct 2026
- 2026LLM Watermarking as Big Data Provenance: A Deployment-Oriented Systematization11 Jul 2026
- 2025Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codes19 Dec 2025
- 2025Watermarking Large Language Models in Europe: Interpreting the AI Act in Light of Technology5 Nov 2025
- 2025Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption21 Oct 2025
- 2025Learning to Watermark: A Selective Watermarking Framework for Large Language Models via Multi-Objective Optimization13 Oct 2025
- 2025PRIVMARK: Private Large Language Models Watermarking with MPC29 Sep 2025
- 2025Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends15 Aug 2025
- 2025In-Context Watermarks for Large Language Models22 May 2025
- 2025Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learning9 Apr 2025
- 2025BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks21 Jan 2025
- 2024SoK: Watermarking for AI-Generated Content27 Nov 2024
12 newest of 20 All 20 (JSON)
- 2024Copyright Protection in Generative AI: A Technical Perspectivecited by 38
- 2023Making Translators Privacy-aware on the User's Sidecited by 3
- 2024User-Side Realizationcited by 3
- 2024Overhead-free User-side Recommender Systemscited by 2
- 2025WaterDrum: Watermarking for Data-centric Unlearning Metriccited by 0
- 2026Preserving Structure, Strengthening Signals: A Grammar-Driven Approach to Optimize the Trade-off Between Quality and Detectability in Code Watermarkingcited by 0
- 2026Preserving Structure, Strengthening Signals: A Grammar-Driven Approach to Optimize the Trade-off Between Quality and Detectability in Code Watermarking11 Jul 2026
- 2025WaterDrum: Watermarking for Data-centric Unlearning Metric8 May 2025
- 2024Overhead-free User-side Recommender Systems12 Nov 2024
- 2024User-Side Realization23 Mar 2024
- 2024Copyright Protection in Generative AI: A Technical Perspective4 Feb 2024
- 2023Making Translators Privacy-aware on the User's Side7 Dec 2023
Similar, not cited
Close in wording, no citation either way
- 2023Mark My Words: Analyzing and Evaluating Language Model Watermarks
- 2025PRO: Enabling Precise and Robust Text Watermark for Open-Source LLMs
- 2024Provably Robust Watermarks for Open-Source Language Models
- 2024A Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules
- 2023On the Learnability of Watermarks for Language Models
- 2024PostMark: A Robust Blackbox Watermark for Large Language Models
- 2024Provably Robust Multi-bit Watermarking for AI-generated Text
- 2025DERMARK: A Dynamic, Efficient and Robust Multi-bit Watermark for Large Language Models