Feb 2, 2023 · We present speculative sampling, an algorithm for accelerating transformer decoding by enabling the generation of multiple tokens from each transformer call. Our …

To mitigate the high inference latency stem- ming from autoregressive decoding in Large Language Models (LLMs), Speculative Decod- ing has emerged as a novel decoding …

Feb 2, 2023 · We benchmark speculative sampling with Chinchilla, a 70 billion parameter language model, achieving a 2-2.5x decoding speedup in a distributed setup, without …

Accelerating Large Language Model Decoding with Speculative Sampling Charlie Chen, Sebastian Borgeaud, Geoffrey Irving, Jean-Baptiste Lespiau, Laurent Sifre, John Jumper. …

Abstract To mitigate the high inference latency stem-ming from autoregressive decoding in Large Language Models (LLMs), Speculative Decod-ing has emerged as a novel decoding paradigm …

Feb 3, 2023 · Speculativesamplingdoesnotrequiremakinganymodificationstothetargetlanguage model’sparametersorarchitecture,isprovablylosslesswithinnumerics,scaleswellwiththeappro- …

Aug 8, 2023 · Recent advances with large language models (LLM) illustrate their diverse capabilities. We propose a novel algorithm, staged speculative decoding, to accelerate LLM …

Abstract Inference with Multimodal Large Language Models (MLLMs) is slow due to their large-language-model backbone which suffers from memory bandwidth bottle-neck and generates …

Unlike autoregressive decoding, Speculative Decoding facilitates the simultaneous decoding of multiple tokens per step, thereby accelerating inference. This paper presents a comprehensive …

Mar 20, 2025 · Speculative decoding has been shown as an effective way to accelerate Large Language Model (LLM) inference by using a Small Speculative Model (SSM) to generate …

Abstract—Speculative decoding has been shown as an effective way to accelerate Large Language Model (LLM) inference using a Small Speculative Model (SSM) to generate …

Abstract Recent advances with large language models (LLM) illustrate their diverse capabilities. We propose a novel algorithm, staged speculative decoding, to accelerate LLM inference in …