2 papers
cs.CV2026
Beyond Binary Preference: Aligning Diffusion Models to Fine-grained Criteria by Decoupling Attributes
Chenye Meng, Zejian Li, Zhongni Liu +9
Post-training alignment of diffusion models relies on simplified signals, such as scalar rewards or binary preferences. This limits alignment with complex human expertise, which is…
cs.CV2025
Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models
Zejian Li, Yize Li, Chenye Meng +7
Recent advancements in diffusion models (DMs) have been propelled by alignment methods that post-train models to better conform to human preferences. However, these approaches typi…