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Discrete Flow Matching: Convergence Guarantees Under Minimal Assumptions
Discrete Flow Matching achieves non-asymptotic KL and total variation convergence bounds under minimal approximation error assumptions with improved scaling in vocabulary size and dimension.
Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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