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A Better Critic Matters for Distribution Matching Distillation

Paper recorded by Signals 4 on 2026-10-30 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-30 on arXiv · recorded by Signals 4 on 2026-11-02

Category: cs.LG · 机器学习 · first seen 2026-11-02

Abstract

Distribution Matching Distillation (DMD) trains a few-step student using the difference between a teacher's score and an online critic's estimate of the student distribution's score. We investigate what the critic needs, in capacity and in information, to provide a reliable training signal. On the capacity side, controlled experiments across seven SiT model sizes on ImageNet show that increasing t

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#51 most recent of 703 cs.LG papers we have recorded · ↑ newer: Counting on Dummies: Privacy Amplification with Observable Counts and · ↓ older: Instance-dependent sequential limits as an exact information ledger
Cite this page: A Better Critic Matters for Distribution Matching Distillation: the #51 most recent of 703 cs.LG papers we have recorded (as of 2026-10-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-better-critic-matters-for-distribution-matching-distillation.html
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