AI RESEARCH
Structured Coupling for Flow Matching
arXiv CS.LG
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ArXi:2605.07676v1 Announce Type: new Standard flow matching scales well but typically relies on an unstructured source distribution, limiting its ability to learn interpretable latent structure. Latent-variable models, by contrast, capture structure but often sacrifice generative quality. We bridge this gap by proposing Structured Coupling for Flow Matching (SCFM), a cooperative framework that augments flow matching with structured latent representation learning. By