MDM-VGB augments masked diffusion with backtracking-style reward-guided remasking to achieve quadratic-complexity high-reward generation and sample editing, with proofs of noise robustness.
Effective test- time scaling of discrete diffusion through iterative refinement.arXiv preprint arXiv:2511.05562,
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LoopMDM loops early-middle layers in masked diffusion models to match same-size MDM performance with up to 3.3x fewer training FLOPs and outperform on reasoning tasks by up to 8.5 points on GSM8K.
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VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing
MDM-VGB augments masked diffusion with backtracking-style reward-guided remasking to achieve quadratic-complexity high-reward generation and sample editing, with proofs of noise robustness.
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Looped Diffusion Language Models
LoopMDM loops early-middle layers in masked diffusion models to match same-size MDM performance with up to 3.3x fewer training FLOPs and outperform on reasoning tasks by up to 8.5 points on GSM8K.