FlashMap: Flow Map Speculative Decoding

Key points

• Autoregressive drafters generate this block one token at a time, whereas block diffusion drafters such as DFlash generate it in one pass, making drafting faster.1
• However, these diffusion drafters predict each token independently, ignoring dependencies between tokens in the block.1
• We introduce FlashMap, a continuous flow drafter that conditions a flow map language model on the target model's hidden states and generates the whole block in one forward pass while capturing inter-token dependencies.1
• On Qwen3-8B, FlashMap is faster than a matched DFlash baseline on every benchmark, with 7% higher average speedup and up to 6.1x lossless acceleration.1

Sources (1)

• [1]FlashMap: Flow Map Speculative Decoding
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 17, 01:32 AM

  Speculative decoding accelerates large language model (LLM) inference by using a lightweight drafter to propose a block of tokens that the target model verifies in one parallel pass.

  Autoregressive drafters generate this block one token at a time, whereas block diffusion drafters such as DFlash generate it in one pass, making drafting faster.

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