AI RESEARCH
A Few-Step Generative Model on Cumulative Flow Maps
arXiv CS.LG
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ArXi:2605.03623v1 Announce Type: new We propose a unified, few-step generative modeling framework based on \emph{cumulative flow maps} for long-range transport in probability space, inspired by flow-map techniques for physical transport and dynamics. At its core is a cumulative-flow abstraction that connects local, instantaneous updates with finite-time transport, enabling generative models to reason about global state transitions.