Text REVISION

Text revision, encompassing tasks like sentence simplification, formalization, and concision improvement, aims to enhance text quality through iterative editing. Current research focuses on developing computational models, often leveraging large language models (LLMs) and incorporating techniques like recursive reprompting, representation optimization, and human-in-the-loop approaches, to improve the accuracy and efficiency of automated revision. These advancements are significant for improving the quality of various text types, from scientific articles and instructional materials to creative writing, and for building more effective writing assistance tools. Furthermore, research is exploring new evaluation metrics and datasets to better assess the performance of these models and understand the nuances of the human revision process.