The Confidence Shortcut: A Reasoning Failure Mode of Masked Diffusion Models
Masked diffusion models use confidence-based decoding, which prioritizes locally easy predictions over logical reasoning order. This causes errors on complex tasks like multi-digit addition where the model takes shortcuts instead of following true dependencies. Training methods that align with this shortcut further amplify these failures, showing that the inference policy must match the task's reasoning flow.