DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding
Speculative decoding accelerates LLM inference by drafting several tokens and verifying them in parallel. Block-diffusion drafters such as DFlash produce a draft block in one pass but model only per-position marginals; best-first tree methods such as DDTree expand candidate trees from those marginals. The released Domino drafter adds a GRU-based causal correction that makes 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-factoriz
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- Linked via arxiv authorSaw S. Lin →
DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding
- Linked via arxiv authorJyh-Shing Roger Jang →
DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding
