Jindong Yang — accepted AI-conference papers

2026

FARI: Robust One-Step Inversion for Watermarking in Diffusion Models

Jindong Yang, Han Fang, Weiming Zhang, Nenghai Yu, Kejiang Chen

ICLR 2026poster

Inversion-based watermarking is a promising approach to authenticate diffusion-generated images, yet practical use is bottlenecked by inversion that is both slow and error-prone. While the primary challenge in the watermarking setting is robustness against external distortions, existing approaches o…

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2025

T2SMark: Balancing Robustness and Diversity in Noise-as-Watermark for Diffusion Models

Jindong Yang, Han Fang, Weiming Zhang, Nenghai Yu, Kejiang Chen

NeurIPS 2025poster

Diffusion models have advanced rapidly in recent years, producing high-fidelity images while raising concerns about intellectual property protection and the misuse of generative AI. Image watermarking for diffusion models, particularly Noise-as-Watermark (NaW) methods, encode watermark as specific s…

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