Generated Rationale

Generated rationales are explanations produced by machine learning models to justify their predictions, enhancing transparency and trustworthiness, particularly in high-stakes domains like healthcare and law. Current research focuses on improving rationale generation using large language models and developing novel architectures, such as unified encoder models, to overcome limitations of traditional two-phase approaches. This work aims to improve model performance and interpretability, leading to more reliable and explainable AI systems with significant implications for various fields requiring decision justification and accountability.