Boosting Large Language Model Inference with Sparse Self-Speculative Decoding

This ArXiv article likely introduces a novel method for improving the efficiency of inference in large language models (LLMs), specifically focusing on techniques like speculative decoding. The research's practical significance lies in its potential to reduce the computational cost and latency associated with LLM deployments.

• •Focuses on improving the inference speed of LLMs.
• •Employs techniques like speculative decoding.
• •Aims to reduce computational cost and latency.