Papers by Ferdinando Fioretto

1 papers
Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion (2025.naacl-long)

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Challenge: Existing methods to accelerate large language model inference are limited by the reliance on incremental token generation in existing draft models.
Approach: They propose an adaptation of speculative decoding which uses discrete diffusion models to generate draft sequences and allows parallelization of both the drafting and verification steps.
Outcome: The proposed approach provides 7.2x speedups over standard generation processes and 1.75x speed ups over existing speculative decoding approaches.

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