Public Exception

"Public exception," in the context of various fields, refers to the handling of instances that deviate from general rules or models. Current research focuses on identifying and mitigating the impact of these exceptions, employing techniques like chain-of-thought prompting with large language models (LLMs) to improve accuracy in tasks such as grading and moral judgment prediction. This work is significant because accurately handling exceptions is crucial for improving the reliability and robustness of AI systems across diverse applications, from education to autonomous driving, and for advancing our understanding of human reasoning and decision-making.