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Renormalization Group Flow Matching for Scalable Local Generative Modeling

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.23696v1 Announce Type: new Abstract: Despite their remarkable success in modeling complex data, generative models face a fundamental tradeoff. Global approaches can capture full structural coherence but suffer from high computational costs, while local models are efficient but often fail…

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  1. 2026-08-26 04:00 · arXiv cs.LG
    Renormalization Group Flow Matching for Scalable Local Generative Modeling

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