CoDR: Training-Free Confidence-Drift Remasking for Diffusion Language Models
EMNLP 2026. Accepted.
Overview
Training-free, sampler-agnostic remasking guided by confidence drift improves accuracy across two diffusion LLMs, three samplers, and four benchmarks, with 76% fewer forward evaluations than ReMDM in a matched setting.