SOURCE-LINKED INTELLIGENCE

Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Aligning video generative models to human preferences heavily relies on Reinforcement Learning (RL), which suffers from extensive computational overhead. Existing workflows typically treat RL and distillation as disconnected stages: applying RL before distillation incurs prohibitive computational costs, whereas applying RL after distillation frequently leads to model collapse. To overcome these limitations, we propose a unified, single-stage optimization framework grounded in Distribution Matching (DM). In the standard DM framework, distillation updates the model via a gradient direction that

Read original source ↗ Open in workspace

recordType

paper

region

Global