4 papers
TextSeal: A Localized LLM Watermark for Provenance & Distillation Protection
Tom Sander, Hongyan Chang, Tomáš SouÄek +10
We introduce TextSeal, a state-of-the-art watermark for large language models. Building on Gumbel-max sampling, TextSeal introduces dual-key generation to restore output diversity,…
How Good is Post-Hoc Watermarking With Language Model Rephrasing?
Pierre Fernandez, Tom Sander, Hady Elsahar +6
Generation-time text watermarking embeds statistical signals into text for traceability of AI-generated content. We explore *post-hoc watermarking* where an LLM rewrites existing t…
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models
Hongyan Chang, Ali Shahin Shamsabadi, Kleomenis Katevas +2
Membership Inference Attacks (MIAs) on pre-trained Large Language Models (LLMs) aim at determining if a data point was part of the model's training set. Prior MIAs that are built f…
Watermark Smoothing Attacks against Language Models
Hongyan Chang, Hamed Hassani, Reza Shokri
Watermarking is a key technique for detecting AI-generated text. In this work, we study its vulnerabilities and introduce the Smoothing Attack, a novel watermark removal method. By…