DLoop: Looped Speculative Decoding
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Computer Science > Computation and Language
arXiv:2610.07659 (cs)
[Submitted on 6 Oct 2026]
Title:DLoop: Looped Speculative Decoding
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Abstract:Speculative decoding accelerates autoregressive generation in large language models. In each drafting stage, a lightweight draft model proposes tokens that the target model subsequently verifies. With increasingly capable draft models, we find that the target model frequently accepts all tokens produced in a drafting stage. A verification nevertheless follows each drafting stage, resulting in unnecessary target-model forward passes even when drafting could have continued. Adaptive draft length methods decide during decoding how many draft tokens precede a verification, but they raise the speedup only for autoregressive draft models. For a parallel draft model, drafting further requires target-model hidden states for draft tokens that have not been verified. We propose DLoop, a looped form of speculative decoding that adaptively performs multiple drafting stages before verification. DLoop continues drafting while the draft model remains confident and verifies all accumulated draft tokens together. Loop-aware training keeps the draft model reliable in the additional drafting stages by exposing it to its own hidden states for unverified draft tokens. By spending additional draft-model forward passes, DLoop reduces the number of target-model forward passes required for verification. Across diverse speculative decoding methods including EAGLE-3, DFlash, Domino, DSpark, and multi-token prediction modules, DLoop improves the wall-clock speedup by 5 to 41 percent while preserving lossless decoding. Code will be available at this https URL.
| Comments: | 22 pages |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.07659 [cs.CL] |
| (or arXiv:2610.07659v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.07659
arXiv-issued DOI via DataCite (pending registration)
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View a PDF of the paper titled DLoop: Looped Speculative Decoding, by Geonmo Gu and 6 other authors
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