Senior Researcher, Huawei Noah's Ark Lab
2 papers at NeurIPS 2025
We present a theoretical framework that interprets masked diffusion models (MDMs) as solutions to energy minimization problems and an efficient post-training schedule tuning method without model modification.
a unified multimodal model purely based on discrete flow matching, achieving comparable performance with AR-based MLLMs
