2026
Unified Customized Generation by Disentangled Reward Modeling
CVPR 2026
Existing literature typically treats various customized generation tasks (e.g., subject-customized generation, style-customized generation) as distinct and disjoint problems, with each task focusing solely on customizing a specific aspect of the reference image. However, we argue that the objectives