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DScale: Scaling Block-Diffusion Speculative Decoding with Adaptive Verification
Growing large language model applications demand efficient inference. At high concurrency, block-diffusion speculative decoding suffers from verification padding, rejected candidates, and incompatibility between variable prefixes and fixed-shape graphs. Uniform truncation sacrifices acceptable token
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