AI RESEARCH
Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
arXiv CS.LG
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ArXi:2509.21912v2 Announce Type: replace Guidance provides a simple and effective framework for posterior sampling by steering the generation process towards the desired distribution. When modeling discrete data, existing approaches mostly focus on guidance with the first-order approximation to improve the sampling efficiency. However, such an approximation is inappropriate in discrete state spaces since the approximation error could be large.