Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies

This paper provides a detailed overview of various techniques used to correct large language models, including training-time, generation-time, and post-hoc correction methods.

It discusses the use of automated feedback from the models themselves or external sources to improve model performance and reduce human intervention.