The authors analyzed the two principal training signals in Distribution Matching Distillation: guidance from a frozen teacher model and a fake-score critic that estimates discrepancies in the student's generated distribution.
Dynamics-aware distillation preserves motion in four-step video world models
DyMD modifies distribution-matching supervision to retain robot-object interactions while compressing video generation into four sampling steps.
Top University
Beihang University · JD Future Academy
Research Digest··2 min read
Xu et al.
Why this paper
From Beihang University and JD Future Academy
In one line
DyMD improves few-step video generation by preserving interaction dynamics via distribution matching distillation.
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