Efficient Adaptive Rejection Sampling for Accelerating Speculative Decoding in Large Language Models

This article likely presents a novel method to improve the speed of speculative decoding, a technique used to accelerate the generation of text in large language models. The focus is on improving the efficiency of the rejection sampling process, which is a key component of speculative decoding. The use of 'adaptive' suggests the method dynamically adjusts parameters for optimal performance.