2026
FOCUS: DLLMs Know How to Tame Their Compute Bound
ICML 2026poster
Diffusion Large Language Models (**DLLMs**) offer a compelling alternative to Auto-Regressive models, but their deployment is constrained by high decoding cost. In this work, we identify a key inefficiency in DLLM decoding: while computation is parallelized over token blocks, only a small subset of …