Free Text Rationale

Free-text rationales are natural language explanations generated by large language models (LLMs) to justify their predictions, aiming to enhance model transparency and trustworthiness. Current research focuses on improving the quality, persuasiveness, and human utility of these rationales, exploring techniques like readability control, prompting strategies, and knowledge distillation to refine their generation and evaluation. This work is significant because it addresses the critical need for interpretability in AI, impacting fields like hate speech detection, question answering, and visual recognition by providing insights into model decision-making processes and potentially improving model performance.