2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Refining Few-Step Text-to-Multiview Diffusion via Reinforcement Learning
Ziyi Zhang, Li Shen, Deheng Ye +5
Text-to-multiview (T2MV) diffusion models have shown great promise in generating multiple views of a scene from a single text prompt. While few-step backbones enable real-time T2MV…
cs.LG2026★ 2 cited
Aligning Few-Step Diffusion Models with Dense Reward Difference Learning
Ziyi Zhang, Li Shen, Sen Zhang +6
Few-step diffusion models enable efficient high-resolution image synthesis but struggle to align with specific downstream objectives due to limitations of existing reinforcement le…
cs.LG2024
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases
Ziyi Zhang, Sen Zhang, Yibing Zhan +3
Bridging the gap between diffusion models and human preferences is crucial for their integration into practical generative workflows. While optimizing downstream reward models has…