RADAR: Novel RL-Based Approach Speeds LLM Inference

This ArXiv paper introduces RADAR, a novel method leveraging Reinforcement Learning to accelerate inference in Large Language Models. The dynamic draft trees offer a promising avenue for improving efficiency in LLM deployments.

• •RADAR employs Reinforcement Learning to create dynamic draft trees.
• •The method aims to significantly improve LLM inference speed.
• •The research is published on ArXiv, indicating early-stage findings.