DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding
Speculative decoding accelerates LLM inference by drafting tokens and verifying them in parallel. Block-diffusion drafters such as DFlash model only per-position marginals, and tree methods such as DDTree expand candidate trees from those marginals. The released Domino drafter adds a GRU-based causal correction making each draft token's distribution path-dependent, a structure DDTree's factorized formulation cannot represent. We introduce DominoTree, a training-free best-first draft tree scored by Domino's conditional (non-factorized) correction along each root-to-node path, made practical by restricting the per-node correction to a candidate top-M. We evaluate it on eight benchmarks in a...
| Authors | Saw S. Lin, Jyh-Shing Roger Jang |
|---|---|
| Primary category | cs.CL |
| Published | 9 July 2026 |
| Last updated at source | 18 August 2026 |
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