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cs.LG2026
Asymmetric On-Policy Distillation: Bridging Exploitation and Imitation at the Token Level
Nan Jia, Haojin Yang, Xing Ma +6
On-policy distillation (OPD) trains a student on its own trajectories with token-level teacher feedback and often outperforms off-policy distillation and standard reinforcement lea…
cs.LG2026
Euphonium: Steering Video Flow Matching via Process Reward Gradient Guided Stochastic Dynamics
Ruizhe Zhong, Jiesong Lian, Xiaoyue Mi +4
While online Reinforcement Learning has emerged as a crucial technique for aligning flow matching models with human preferences, current approaches are hindered by inefficient expl…
cs.LG2025
SoliReward: Mitigating Susceptibility to Reward Hacking and Annotation Noise in Video Generation Reward Models
Jiesong Lian, Ruizhe Zhong, Zixiang Zhou +6
Post-training alignment of video generation models with human preferences is a critical goal. Developing effective Reward Models (RMs) for this process faces significant methodolog…