arXiv AI August 14, 2026 By Malte Hellmeier

Security and Detectability Analysis of Unicode Text Watermarking Methods against Large Language Models

arXiv:2512. 13325v2 Announce Type: replace-cross Abstract: Securing digital text is becoming increasingly relevant due to the widespread use of large language models.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Machine Learning

Aug 31

OpenStamp: A Watermark for Open-Source Language Models

arXiv:2608.27899v1 Announce Type: cross Abstract: With the growing prevalence of large language model (LLM) generated content, watermarking is considered a promising approach for attributing text to...

By Miroojin Bakshi, Saksham Rastogi, Danish Pruthi

llms fine-tuning

arXiv Machine Learning

Aug 12

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign

arXiv:2502. 02068v3 Announce Type: replace-cross Abstract: This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid intellectual property rights violations and inappropriate misuse in software development.

By Ruisi Zhang, Neusha Javidnia, Nojan Sheybani, Farinaz Koushanfar

llms

arXiv Machine Learning

Sep 23

The Challenge of Identifying the Origin of Black-Box Large Language Models

arXiv:2503.04332v2 Announce Type: replace-cross Abstract: The tremendous commercial potential of large language models (LLMs) has heightened concerns over their unauthorized use. To address this, we...

By Ziqing Yang, Yixin Wu, Yun Shen, Wei Dai, Michael Backes, Yang Zhang

llms rag benchmarks safety

arXiv Machine Learning

Jun 18

Signature filtering: a lightweight enhancement for statistical watermark detection in large language models

arXiv:2606. 18430v1 Announce Type: new Abstract: Statistical watermarks help organizations attribute large language model (LLM) outputs, yet existing detectors often struggle when watermark signals are weak, texts are repetitive, or watermarks are edited.

By Chih-Duo Hong, Yen-Pang Chen, Fang Yu

llms rag benchmarks

arXiv AI

Jul 7

Selective Disclosure Watermarking for Large Language Models

arXiv:2607. 05353v1 Announce Type: cross Abstract: Watermarking methods embed imperceptible and verifiable signals into text generated by large language models (LLMs).

By Xuyang Chen, Xiang Li, Yangxinyu Xie, Qi Long

llms rag safety

arXiv AI

Jun 11

T2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking

arXiv:2606. 11698v1 Announce Type: cross Abstract: Model watermarking safeguards AI model intellectual property by embedding distinctive knowledge that induces unique behavioral signatures.

By Jian-Ping Mei, Weibin Zhang, Ao Yao, Tiantian Zhu, Jie Xiao

rag fine-tuning

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Related stories

OpenStamp: A Watermark for Open-Source Language Models

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign

The Challenge of Identifying the Origin of Black-Box Large Language Models

Signature filtering: a lightweight enhancement for statistical watermark detection in large language models

Selective Disclosure Watermarking for Large Language Models

T2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking