Fast Collaborative Inference via Distributed Speculative Decoding

This article likely presents a novel approach to accelerate the inference process in large language models (LLMs). The focus is on distributed speculative decoding, which suggests a method to parallelize and speed up the generation of text. The use of 'collaborative' implies a system where multiple resources or agents work together to achieve faster inference. The source, ArXiv, indicates this is a research paper, likely detailing the technical aspects, experimental results, and potential advantages of the proposed method.