AI RESEARCH
STDec: Spatio-Temporal Stability Guided Decoding for dLLMs
arXiv CS.CL
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ArXi:2604.06330v1 Announce Type: new Diffusion Large Language Models (dLLMs) have achieved rapid progress, viewed as a promising alternative to the autoregressive paradigm. However, most dLLM decoders still adopt a global confidence threshold, and do not explicitly model local context from neighboring decoded states or temporal consistency of predicted token IDs across steps. To address this issue, we propose a simple spatio-temporal stability guided decoding approach, named STDec.