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AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation research paper by NVIDIA, 2026

NVIDIA · May 13, 2026 · Multimodal and robotics · 15 citations · 103 upvotes · unverified

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What it shows

AnyFlow introduces a novel any-step video diffusion distillation framework that improves upon consistency distillation by optimizing full ODE sampling trajectories through flow-map transition learning and backward simulation techniques.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Yuchao Gu, Guian Fang, Yuxin Jiang and 4 more
arXiv
2605.13724 · PDF
Venue
arXiv.org
Citations
15, 4 influential · Semantic Scholar
Upvotes
103 · Hugging Face
Code
github.com/NVlabs/AnyFlow
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 4Sep 25, 2026
Citationsfirst count: 15Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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