arXiv Machine Learning June 25, 2026 By Sahil Kadadekar

Speculative Decoding at Temperature Zero: A Scoped Safety-Invariance Screen with a 48,072-Sample Expansion

Read the original on arXiv Machine Learning →

arXiv:2606. 25097v1 Announce Type: new Abstract: Speculative decoding accelerates inference by letting a draft model propose tokens for a target model to verify, raising a concrete safety question: at temperature zero, can draft-side behavior leak into safety-scored outputs?

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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