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Jerrum-Sinclair backtracking Markov chain

techniqueactiveprovisionaljerrum-sinclair-backtracking-markov-chain-5b04d97c·1 events·first seen 17h ago

Aliases: Jerrum-Sinclair backtracking Markov chain

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5arXiv · cs.LG·17h ago·source ↗

MDM-VGB: Theoretically grounded test-time scaling for masked diffusion models via reward-guided remasking

Researchers introduce MDM-VGB, a discrete diffusion sampler for Masked Diffusion Models that augments token unmasking with reward-guided remasking inspired by the Jerrum-Sinclair backtracking Markov chain. The method extends backtracking from a fixed prefix tree to a masked-state graph, enabling tokens to be unmasked and remasked at arbitrary positions to favor higher-reward partial configurations. The authors prove quadratic complexity and robustness to process-verifier noise, contrasting with exponential complexity of best-of-N heuristics, and validate on constraint-satisfaction benchmarks including Sudoku and QM9.