Author

Yufeng Zhang

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Preprint Jul 2026

CORA-Diff: Confidence-Oriented Residual Acceptance for Efficient Diffusion Language Model Inference

This work proposes CORA-Diff, a training-free method that preserves the original transfer rule and applies confidence-and-persistence gating only to positions that rule leaves unresolved, and shows that native confidence and persistence enable reliable residual acceptance, reducing repeated denoising computation while preserving task quality.

Yifan Wu, Yufeng Zhang, Kenli Li · 0 citations