5 papers
Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio
Georgios Milis, Yubin Qin, Yihan Wu +1
As policy catches up with the capabilities of generative AI, watermarking is central to content provenance efforts. Inference-time watermarks for autoregressive models are unfit fo…
Compositional Adversarial Training for Robust Visual Watermarking
Anirudh Satheesh, Michael-Andrei Panaitescu-Liess, Andrew Xu +4
Robust watermarking is typically trained with random post-processing augmentation, but random sampling under-covers the combinatorial space of realistic attack pipelines and rarely…
Robust Distortion-Free Watermark for Autoregressive Audio Generation Models
Yihan Wu, Georgios Milis, Ruibo Chen +1
The rapid advancement of next-token-prediction models has led to widespread adoption across modalities, enabling the creation of realistic synthetic media. In the audio domain, whi…
An Ensemble Framework for Unbiased Language Model Watermarking
Yihan Wu, Ruibo Chen, Georgios Milis +1
As large language models become increasingly capable and widely deployed, verifying the provenance of machine-generated content is critical to ensuring trust, safety, and accountab…
A Watermark for Auto-Regressive Image Generation Models
Yihan Wu, Xuehao Cui, Ruibo Chen +2
The rapid evolution of image generation models has revolutionized visual content creation, enabling the synthesis of highly realistic and contextually accurate images for diverse a…