Stabilizing Reinforcement Learning with LLMs: Formulation and Practices

The article likely explores methods to improve the stability of Reinforcement Learning (RL) algorithms by leveraging Large Language Models (LLMs). This could involve using LLMs for tasks like state representation, action selection, or reward shaping. The focus is on both the theoretical formulation and practical implementation of these techniques.