arxiv
PublishedNovember 2, 2026 at 5:00 AM
Cumulative Marginal Matching for One-Step Diffusion
Publisher summary· verbatim
arXiv:2610.34575v2 Announce Type: replace Abstract: The sampling procedures of diffusion and flow-matching models involve hundreds of denoising steps incurring substantial inference time, which has motivated a growing body of work on training schemes for few-step and one-step generation. Existing ap
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivEnhancing Sentiment Classification on Small Datasets through Data Augmentation and Transfer Learning8harxivComparative Evaluation of LLM-Based Review Paradigms for Academic Paper Quality Assessment8harxivBlindToChange: AI Agents Can Find Changes When Asked But Do They Look When Needed?8harxivDAPS: Dependency-Aware Premise Selection for LLM Theorem Proving8hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗