This method improves Diffusion Language Model (DLM) quality by using frequency-aware remasking during inference. It identifies tokens that change frequently during denoising steps and preferentially commits them, allowing the model to spend more compute on difficult reasoning tasks.
HOW THIS AFFECTS YOU
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researcherYou can improve DLM performance on hard problems by allocating more decoding compute to uncertain tokens.