DCOCO restores intra-block dependencies in speculative decoding with up to 6.6x speedup
Roy Eisenstadt · hf · 2026-10-12
The paper introduces DCOCO (DFlash Contextual Corrector), addressing a key weakness of diffusion-based speculative decoding: draft tokens are predicted in parallel without access to preceding draft tokens, losing intra-block dependencies. DCOCO retains multiple candidate tokens per position and scores their contextual compatibility across adjacent draft positions in parallel, enabling contextually informed selection at low cost. Across 4 verifier backbones and 10 benchmarks, it achieves the highest average throughput in every configuration (greedy/stochastic, with/without extended reasoning), with up to 6.6x speedup over vanilla decoding; under concurrent serving (4-32 requests) it beats the strongest competing method by 6-23%, while sequential correctors fall below uncorrected DFlash at high load.
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