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arXiv · 2602.20463

A Long-Short Flow-Map Perspective for Drifting Models

Zhiqi Li·Bo Zhu
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Abstract

This paper provides a reinterpretation of the Drifting Model~\cite{deng2026generative} through a semigroup-consistent long-short flow-map factorization. We show that a global transport process can be decomposed into a long-horizon flow map followed by a short-time terminal flow map admitting a closed-form optimal velocity representation, and that taking the terminal interval length to zero recovers exactly the drifting field together with a conservative impulse term required for flow-map consistency. Based on this perspective, we propose a new likelihood learning formulation that aligns the long-short flow-map decomposition with density evolution under transport. We validate the framework through both theoretical analysis and empirical evaluations on benchmark tests, and further provide a theoretical interpretation of the feature-space optimization while highlighting several open problems for future study.

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Zhiqi Li, Bo Zhu. 2026-02-24. A Long-Short Flow-Map Perspective for Drifting Models. https://arxiv.org/abs/2602.20463

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