61 citations · 110 across the 57 of their papers we have counts for
8 papers · 1 filter
Preserving Structure, Strengthening Signals: A Grammar-Driven Approach to Optimize the Trade-off Between Quality and Detectability in Code Watermarking
Licheng Yu, Aiwei Liu, Songze Li
Text watermarking has emerged as a crucial technique for identifying AI-generated content. However, current watermarking schemes entail a trade-off between text quality and waterma…
MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models
Leyi Pan, Sheng Guan, Zheyu Fu +9
We introduce MarkDiffusion, an open-source Python toolkit for generative watermarking of latent diffusion models. It comprises three key components: a unified implementation framew…
PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraints
Jiahao Huo, Shuliang Liu, Bin Wang +5
Semantic-level watermarking (SWM) for large language models (LLMs) enhances watermarking robustness against text modifications and paraphrasing attacks by treating the sentence as…
MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection
Liancheng Fang, Aiwei Liu, Henry Peng Zou +4
We introduce MUSE, a watermarking algorithm for tabular generative models. Previous approaches typically leverage DDIM invertibility to watermark tabular diffusion models, but tabu…
VideoMark: A Distortion-Free Robust Watermarking Framework for Video Diffusion Models
Xuming Hu, Hanqian Li, Jungang Li +5
This work introduces \textbf{VideoMark}, a distortion-free robust watermarking framework for video diffusion models. As diffusion models excel in generating realistic videos, relia…
Can Watermarked LLMs be Identified by Users via Crafted Prompts?
Aiwei Liu, Sheng Guan, Yiming Liu +6
Text watermarking for Large Language Models (LLMs) has made significant progress in detecting LLM outputs and preventing misuse. Current watermarking techniques offer high detectab…
MarkLLM: An Open-Source Toolkit for LLM Watermarking
Leyi Pan, Aiwei Liu, Zhiwei He +9
LLM watermarking, which embeds imperceptible yet algorithmically detectable signals in model outputs to identify LLM-generated text, has become crucial in mitigating the potential…
A Semantic Invariant Robust Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu +2
Watermark algorithms for large language models (LLMs) have achieved extremely high accuracy in detecting text generated by LLMs. Such algorithms typically involve adding extra wate…