arxiv preprint – Re-Reading Improves Reasoning in Large Language Models

In this episode, we discuss Re-Reading Improves Reasoning in Large Language Models by Xiaohan Xu, Chongyang Tao, Tao Shen, Can Xu, Hongbo Xu, Guodong Long, Jian-guang Lou. The paper presents a novel prompting method called RE2 (Re-Reading) that improves the reasoning capabilities of Large Language Models by processing questions twice for better understanding. Unlike conventional methods like Chain-of-Thought, RE2 enhances input processing and facilitates bidirectional encoding in unidirectional models. The method demonstrates improved performance across various reasoning benchmarks and shows compatibility and adaptability with different models and prompting strategies.