arxiv Preprint – Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies

In this episode we discuss Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies
by Liangming Pan, Michael Saxon, Wenda Xu, Deepak Nathani, Xinyi Wang, William Yang Wang. The paper provides a comprehensive review of self-correction strategies for large language models (LLMs). It examines recent work on self-correction techniques, categorizing them into training-time, generation-time, and post-hoc correction methods. The authors also discuss the applications of self-correction and highlight future directions and challenges in this area.