DualDiffusion proposes a speculative decoding strategy to optimize inference speed for masked diffusion models. The approach aims to reduce computation during the iterative denoising process.
Research
DualDiffusion: A Speculative Decoding Strategy for Masked Diffusion Models
DualDiffusion accelerates masked diffusion model inference by speculatively predicting multiple denoising steps in parallel, reducing the total number of iterations needed.
Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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