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Matan Kalman

Faster LLM inference via speculative decoding

Researcher at Google Research working on faster inference and transformer efficiency

An important systems page because he is one of the named authors on speculative decoding, a technique that became part of the mainstream conversation about making large-model inference materially faster without changing outputs.

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Google Research

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01

Speculative decoding

02

Faster transformer inference

03

Efficiency-oriented model design

04

Faster LLM inference via speculative decoding

05

Fast Inference from Transformers via Speculative Decoding

06

Inference

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A high-signal researcher for the latency and systems side of modern language models, especially where clever decoding tricks turn frontier models into usable products.

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Yossi Matias

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Important because his profile sits at the intersection of field-level research leadership and concrete systems work such as speculative decoding that directly changed how modern LLM inference gets deployed.

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