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discrete flow matching

topic2 events
papersTODAY 04:00 UTC

Revisable CTMC Inference Stack Proposed for Guided Discrete Flow Matching TTS

A new arXiv paper introduces a mask-sample-revise inference pipeline built on continuous-time Markov chains for guided discrete flow matching in text-to-speech. The approach targets alignment-free non-autoregressive TTS systems that treat synthesis as conditional infilling over neural codec tokens, avoiding separate duration predictors and external aligners. It proposes letting the sampling process revisit and correct earlier token decisions during generation.

text-to-speech/diffusion/arxiv/codec-tokens
papersSEP 11 04:00 UTC

Paper links continuous and discrete flow matching through argmax projection

A new arXiv preprint argues that continuous and discrete flow matching, typically developed as separate frameworks, are dual formulations of the same underlying construction. The authors show that applying a position-wise argmax to continuous convex-interpolant flows with one-hot targets recovers the discrete counterpart, and they examine how the choice of source distribution shapes categorical generation. A revised version of the submission has replaced the initial preprint.

flow-matching/generative-models/discrete-diffusion/research