collaborators

14 papers

cs.LG2026

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…

cs.SD2026

EnvTriCascade: An Environment-Aware Tri-Stage Cascaded Framework for ESDD2 2026 Challenge

Hengyan Huang, Xiaoxuan Guo, Jiayi Zhou +5

ADD in real-world scenarios has evolved from speech-only spoofing to more challenging component-level settings, where speech and environmental sounds may be independently manipulat…

cs.CV2026

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…

cs.CV2026

Unsafe by Reciprocity: How Generation-Understanding Coupling Undermines Safety in Unified Multimodal Models

Kaishen Wang, Heng Huang

Recent advances in Large Language Models (LLMs) and Text-to-Image (T2I) models have led to the emergence of Unified Multimodal Models (UMMs), where multimodal understanding and ima…

cs.CV2026

ImAgent: A Unified Multimodal Agent Framework for Test-Time Scalable Image Generation

Kaishen Wang, Ruibo Chen, Tong Zheng +1

Recent text-to-image (T2I) models have made remarkable progress in generating visually realistic and semantically coherent images. However, they still suffer from randomness and in…

cs.CV2026

Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following

Tianyi Xiong, Yi Ge, Ming Li +13

Large multimodal models (LMMs) are increasingly adopted as judges in multimodal evaluation systems due to their strong instruction following and consistency with human preferences.…