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Decoupled Contrastive Decoding via Expert-Aligned Drafting

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Computer Science > Computation and Language

arXiv:2608.12913 (cs)
[Submitted on 13 Aug 2026]

Title:Decoupled Contrastive Decoding via Expert-Aligned Drafting

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Abstract:Contrastive Decoding (CD) improves generation quality, but its amateur-model pass makes decoding expensive. Accelerating CD with speculative decoding raises a proposal-alignment question: should the contrastive signal shape the drafter, or should it remain only in verification? We study this question in the lightweight feature-level drafter regime. Two controlled diagnostics, matched Cross-alpha training and an Approximate Dual-Drafter decomposition, give the same diagnosis: contrastive-aware drafting does not consistently improve over expert-aligned drafting because the contrastive correction is usually weaker than drafter error, and reconstruction can amplify that error. We introduce Decoupled Contrastive Decoding (DCD), which drafts with an expert-aligned lightweight proposer and applies the amateur only in unchanged CD verification. Standard speculative verification preserves the vanilla-CD output distribution. Across the main 8B settings, EAGLE3-based DCD achieves average greedy speedups of 1.65 to 1.95x over vanilla CD and reduces MMLU proposal-path latency by about 5 to 12x relative to amateur-coupled proposal paths.
Comments: 28 pages, 11 figures, 20 tables. Code: this https URL
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2608.12913 [cs.CL]
  (or arXiv:2608.12913v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2608.12913
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Zhixuan Liu [view email]
[v1] Thu, 13 Aug 2026 07:56:16 UTC (148 KB)
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