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News/StraightDP: Geometry-Aware Differential Privacy for Rectified-Flow Transformers
arxiv
PublishedAugust 3, 2026 at 4:00 AM

StraightDP: Geometry-Aware Differential Privacy for Rectified-Flow Transformers

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Publisher summary· verbatim

arXiv:2607.29100v1 Announce Type: new Abstract: Differentially private (DP) training of text-conditioned generative models suffers a utility cliff at strong privacy. We revisit this problem through the geometry of rectified flows: along the straight interpolation between noise and data, the Bayes-op

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