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Wednesday, 4 November 2026
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TENESYS AI NEWS tracks the most important AI news and explains what changed, why it matters and whether a technology is worth testing.

#Algorithms — 1 article ✕

Research· 🧪 Worth Testing

Optimizing Multi-Draft Speculative Decoding Efficiency

Researchers have developed a method to calculate the theoretical upper bound for Multi-Draft Speculative Decoding (MDSD) efficiency by solving the dual of the optimal transport problem. The study reveals that current verification algorithms often fall short of this theoretical limit, and that sampling without replacement significantly improves acceptance rates compared to sampling with replacement.

arXiv cs.CL