arXiv Artificial Intelligence

Entropy-Aware Token Rejection for Improving Speculative Decoding

9 days ago 01.09.2026 07:00 👁 2 views
Entropy-Aware Token Rejection for Improving Speculative Decoding

Quick summary

arXiv:2512.23765v2 Announce Type: replace-cross Abstract: Speculative decoding (SD) accelerates large language model (LLM) inference by using a lightweight draft model to propose tokens and a stronger target model to verify them. However, standard SD is mainly designed for acceleration, and its output quality is typically constrained by the target model. In this work, we propose Entropy-Aware Speculative Decoding (EASD), a lightweight and training-free extension of SD that improves reasoning quality through token-level entropy-guided rejection. EASD detects cases where both draft and target mo

Key takeaways

  • arXiv:2512.23765v2 Announce Type: replace-cross Abstract: Speculative decoding (SD) accelerates large language model (LLM) inference by using a lightweight draft model to propose tokens and a stronger target model to verify them.
  • However, standard SD is mainly designed for acceleration, and its output quality is typically constrained by the target model.
  • In this work, we propose Entropy-Aware Speculative Decoding (EASD), a lightweight and training-free extension of SD that improves reasoning quality through token-level entropy-guided rejection.

Why it matters

“Entropy-Aware Token Rejection for Improving Speculative Decoding” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗