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Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching
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video generationreinforcement learningdistillationdistribution matching
2609.04283
Builder Relevance
7h ago80%
Abstract
The paper proposes a unified optimization framework for video generation that aligns models with human preferences while reducing computational overhead.
Reality Card
Core Claim
The proposed DM-Align framework synergizes gradient directions to enhance distillation quality and preference alignment without the need for multi-step reward evaluation.
Method / Result
The framework consistently outperforms standalone variants and sequential two-stage pipelines in comprehensive experiments.
Limitations
The paper does not specify authors or detailed experimental setups, which may hinder reproducibility.
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