collaborators

13 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.CR2026

MCMark: Distortion-Free Multi-Bit Watermarking for Long Messages

Xuehao Cui, Ruibo Chen, Yihan Wu +1

Large language models now produce text indistinguishable from human writing, which increases the need for reliable provenance tracing. Multi-bit watermarking can embed identifiers…

cs.CR2026

More Haste, Less Speed: Weaker Single-Layer Watermark Improves Distortion-Free Watermark Ensembles

Ruibo Chen, Yihan Wu, Xuehao Cui +2

Watermarking has emerged as a crucial technique for detecting and attributing content generated by large language models. While recent advancements have utilized watermark ensemble…

cs.SD2025

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…

cs.LG2025

Modality-Balancing Preference Optimization of Large Multimodal Models by Adversarial Negative Mining

Chenxi Liu, Tianyi Xiong, Yanshuo Chen +5

The task adaptation and alignment of Large Multimodal Models (LMMs) have been significantly advanced by instruction tuning and further strengthened by recent preference optimizatio…

cs.LG2025

Model Correlation Detection via Random Selection Probing

Ruibo Chen, Sheng Zhang, Yihan Wu +3

The growing prevalence of large language models (LLMs) and vision-language models (VLMs) has heightened the need for reliable techniques to determine whether a model has been fine-…