Critique ability, i.e., the capability of Large Language Models (LLMs) to identify

Goal misalignment, reward sparsity and difficult credit assignment are only a few of the many issues that make it difficult for deep reinforcement learning (RL) agents to learn optimal policies.

In particular, most existing work only theoretically explains how the attention mechanism facilitates ICL under certain data models.