mlsanityData to 14 Oct 2026

ByteMark: A Unified Byte-Level Watermark for Detection Across Language Models

arXiv 2610.14427 ↗First posted 10 Oct 2026cs.CR cs.LG stat.MLcited by 0

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

Abstract (arXiv)

As watermarking of LLM-generated text enters deployment, users increasingly need to check text whose source is unknown. Existing detectors read the watermark through a specific tokenizer or embedding pipeline, and even if all providers adopted the same watermarking method, differences in these representations would leave their watermarks incompatible, and the text alone does not reveal which representation produced it. We propose ByteMark, a unified watermarking scheme that defines its signal on the UTF-8 bytes of published text. Models with different tokenizers embed this signal under one public specification and key, and a single detector verifies the text from the text and key alone. When the tokenizer or embedding model of a baseline detector is replaced, its detection degrades sharply, whereas ByteMark, which uses neither, retains its detection rate; ByteMark also remains detectable when participating models continue or rewrite the text.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Watermarking generated content and models, one of 12 directions in LLM safety and security. Builds on 44 of its 64 references that are in the map. First posted on arXiv 10 Oct 2026.

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44 of 64 references.

Closest ancestors · 21

Same direction, newest first

  1. 2026Semantic Watermarking with Order-Robust Detection over Sub-sentence Units27 Aug
  2. 2026Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking6 Jul
  3. 2026Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings30 Jun
  4. 2026AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing28 May
  5. 2026SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness25 May
  6. 2025PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraints25 Sep
  7. 2025BiMark: Unbiased Multilayer Watermarking for Large Language Models19 Jun
  8. 2025Improved Unbiased Watermark for Large Language Models16 Feb
  9. 2025SimMark: A Robust Sentence-Level Similarity-Based Watermarking Algorithm for Large Language Models5 Feb
  10. 2024Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models21 Feb
  11. 2024k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text17 Feb
  12. 2023A Robust Semantics-based Watermark for Large Language Model against Paraphrasing15 Nov
9 more
  1. 2023Embarrassingly Simple Text Watermarks13 Oct
  2. 2023A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models11 Oct
  3. 2023A Semantic Invariant Robust Watermark for Large Language Models10 Oct
  4. 2023Unbiased Watermark for Large Language Models22 Sep
  5. 2023Robust Distortion-free Watermarks for Language Models28 Jul
  6. 2023Three Bricks to Consolidate Watermarks for Large Language Models26 Jul
  7. 2023Provable Robust Watermarking for AI-Generated Text30 Jun
  8. 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense23 Mar
  9. 2023A Watermark for Large Language Models24 Jan

Other references · 23

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2024Qwen2.5 Technical Reportcited by 4,942
  4. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
  5. 2016Pointer Sentinel Mixture Modelscited by 3,096
  6. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
  7. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  8. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  9. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,786
  10. 2025Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Modelscited by 1,261
  11. 2023DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvaturecited by 726
  12. 2024TinyLlama: An Open-Source Small Language Modelcited by 618
11 more
  1. 2024NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Modelscited by 472
  2. 2021Large Dual Encoders Are Generalizable Retrieverscited by 456
  3. 2024Mixture-of-Agents Enhances Large Language Model Capabilitiescited by 438
  4. 2022One Embedder, Any Task: Instruction-Finetuned Text Embeddingscited by 333
  5. 2023Improving Text Embeddings with Large Language Modelscited by 303
  6. 2024RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectorscited by 163
  7. 2024Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating Worldcited by 52
  8. 2024People cannot distinguish GPT-4 from a human in a Turing testcited by 48
  9. 2026How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Taskscited by 33
  10. 2025CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Qualitycited by 19
  11. 2026Token Economics for LLM Agents: A Dual-View Study from Computing and Economicscited by 6

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  1. 2026Tokenization-Invariant Watermarking: A Byte-Local Method for LLM Text
  2. 2025DERMARK: A Dynamic, Efficient and Robust Multi-bit Watermark for Large Language Models
  3. 2024PostMark: A Robust Blackbox Watermark for Large Language Models
  4. 2024A Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules
  5. 2025PRO: Enabling Precise and Robust Text Watermark for Open-Source LLMs
  6. 2026OpenStamp: A Watermark for Open-Source Language Models
  7. 2023Mark My Words: Analyzing and Evaluating Language Model Watermarks
  8. 2026Signature filtering: a lightweight enhancement for statistical watermark detection in large language models