SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness

• URL: http://arxiv.org/abs/2605.25796v1
• Date: Mon, 25 May 2026 12:46:15 GMT
• Title: SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness
• Abstract summary: robustness to paragraph-level paraphrasing remains difficult because such attacks globally disrupt watermark signals by changing sentence order.<n>We propose SAMark, a self-anchored watermarking framework that removes the dependency on sentence order by establishing a step-independent green region in semantic space.<n> Experimental results show that SAMark achieves up to 90.2% TP@FP1% under typical paragraph-level paraphrasing attacks.
• Score: 71.08096624551246
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Semantic-level watermarking (SWM) improves robustness against text modifications by treating sentences as the basic unit. However, robustness to paragraph-level paraphrasing remains difficult because such attacks globally disrupt watermark signals by changing sentence order. In this work, we propose SAMark, a self-anchored watermarking framework that removes the dependency on sentence order by establishing a step-independent green region in semantic space. To improve detectability, we introduce a multi-channel hyperbolic scoring mechanism that amplifies watermark signals while suppressing noise from weakly aligned candidates. We further propose a diversity-aware filtering strategy that combines hard filtering with soft regularization, extending beyond simple n-gram repetition filters to address semantic redundancy. Experimental results show that SAMark achieves up to 90.2% TP@FP1% under typical paragraph-level paraphrasing attacks, outperforming the strongest prior baseline by more than 30% on average, while maintaining generation quality competitive with unwatermarked text and breaking the robustness-quality trade-off that limits prior methods.

Related papers

• AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing [55.03371974830747]
  AliMark is a framework that reformulates sentence-level watermarking as a bit sequence encoding and alignment problem.<n>We show that AliMark substantially outperforms state-of-the-art baselines under diverse paraphrasing attacks.
  arXiv  Detail & Related papers  (2026-05-28T06:30:43Z)
• More Haste, Less Speed: Weaker Single-Layer Watermark Improves Distortion-Free Watermark Ensembles [58.941305935872265]
  We show that strong watermarks significantly reduce the entropy of the token distribution.<n>We propose a framework that utilizes weaker single-layer watermarks to preserve the entropy required for effective multi-layer ensembling.
  arXiv  Detail & Related papers  (2026-02-12T10:18:16Z)
• An Ensemble Framework for Unbiased Language Model Watermarking [60.99969104552168]
  We propose ENS, a novel ensemble framework that enhances the detectability and robustness of unbiased watermarks.<n>ENS sequentially composes multiple independent watermark instances, each governed by a distinct key, to amplify the watermark signal.<n> Empirical evaluations show that ENS substantially reduces the number of tokens needed for reliable detection and increases resistance to smoothing and paraphrasing attacks.
  arXiv  Detail & Related papers  (2025-09-28T19:37:44Z)
• PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraints [49.2373408329323]
  We introduce a new theoretical framework on watermark-leveling (SWM) for large language models (LLMs)<n>We propose PMark, a simple yet powerful SWM method that estimates the median next sentence dynamically through sampling channels.<n> Experimental results show that PMark consistently outperforms existing SWM baselines in both text quality and paraphrasing.
  arXiv  Detail & Related papers  (2025-09-25T12:08:31Z)
• CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Quality [15.40847234599879]
  CoheMark exploits the cohesive relationships between sentences for better logical fluency.<n>CoheMark achieves strong watermark strength while exerting minimal impact on text quality.
  arXiv  Detail & Related papers  (2025-04-24T07:08:13Z)
• Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learning [34.76886510334969]
  A piggyback attack can maliciously alter the meaning of watermarked text-transforming it into hate speech-while preserving the original watermark.<n>We propose a semantic-aware watermarking algorithm that embeds watermarks into a given target text while preserving its original meaning.
  arXiv  Detail & Related papers  (2025-04-09T04:38:17Z)
• SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation [72.10931780019297]
  Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. We propose SemStamp, a robust sentence-level semantic watermarking algorithm based on locality-sensitive hashing (LSH) Experimental results show that our novel semantic watermark algorithm is not only more robust than the previous state-of-the-art method on both common and bigram paraphrase attacks, but also is better at preserving the quality of generation.
  arXiv  Detail & Related papers  (2023-10-06T03:33:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.