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ReSFlow: Rectifying Categorical Flows on Statistical Manifolds for One-Step Generation
Generative modeling for discrete data has been significantly advanced by learning continuous vector fields on the statistical manifolds to transport simple priors to target discrete distributions. However, because these continuous-time flows are not constrained to follow geodesics on the statistical
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