Confidence-based decoding and training in masked diffusion models shortcut long-range dependencies in reasoning, producing errors on complex inputs that random masking avoids.
Where-to-unmask: Ground- truth-guided unmasking order learning for masked diffusion language models.arXiv preprint arXiv:2602.09501, 2026
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
OALMs exhibit order-dependent likelihoods up to 0.49 nats/token and a uniform confidence spread maximizes recoverability, motivating Var(log q_t) as a decoding diagnostic.
citing papers explorer
-
The Confidence Shortcut: A Reasoning Failure Mode of Masked Diffusion Models
Confidence-based decoding and training in masked diffusion models shortcut long-range dependencies in reasoning, producing errors on complex inputs that random masking avoids.
-
Decoding in Order-Agnostic Language Models: Chain-Rule Deviation and Uniform Spreading
OALMs exhibit order-dependent likelihoods up to 0.49 nats/token and a uniform confidence spread maximizes recoverability, motivating Var(log q_t) as a decoding diagnostic.