3 papers
cs.LG2026
Path-Coupled Bellman Flows for Distributional Reinforcement Learning
Boyang Xu, Qing Zou, Siqin Yang +1
Distributional reinforcement learning (DRL) models the full return distribution, but existing finite-support or quantile-based methods rely on projections, while recent flow-based…
cs.CV2026
Continuous-Time Distribution Matching for Few-Step Diffusion Distillation
Tao Liu, Hao Yan, Mengting Chen +8
Step distillation has become a leading technique for accelerating diffusion models, among which Distribution Matching Distillation (DMD) and Consistency Distillation are two repres…
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…