Reinforcement Learning for LLMs
Large language models after pre-training can generate fluent text but may produce responses that are confidently wrong or unhelpful, prompting the use of reinforcement learning to optimize for overall response quality rather than just token likelihood. The core challenge involves credit assignment—determining which specific tokens in a lengthy response contributed to the final reward score. This guide explains how...