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cs.CV2026
DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching
Chang Zou, Changlin Li, Yang Li +7
While diffusion models have achieved great success in the field of video generation, this progress is accompanied by a rapidly escalating computational burden. Among the existing a…
cs.CV2026
UniX: Unifying Autoregression and Diffusion for Chest X-Ray Understanding and Generation
Ruiheng Zhang, Jingfeng Yao, Huangxuan Zhao +9
Despite recent progress, medical foundation models still struggle to unify visual understanding and generation, as these tasks have inherently conflicting goals: semantic abstracti…
cs.CV2026
APEX: Learning Adaptive Priorities for Multi-Objective Alignment in Vision-Language Generation
Dongliang Chen, Xinlin Zhuang, Junjie Xu +8
Multi-objective alignment for text-to-image generation is commonly implemented via static linear scalarization, but fixed weights often fail under heterogeneous rewards, leading to…