Scalable and Robust Watermarking for Diffusion Models via Task-Decoupled Mixture-of-Watermarks

With the growing deployment of text-to-image diffusion models in real-world applications, concerns about model copyright have become increasingly prominent. Model watermarking has emerged as a promising solution. However, existing methods often suffer from degradation of model fidelity and poor scalability in model distribution scenarios. Moreover, recent studies have shown that some watermarking approaches lack robustness against ambiguity attacks. To address these challenges, we propose TD-MoW