Error Understanding

Error Understanding is a subtask under Reasoning, focusing on identifying and analyzing the reasons behind incorrect predictions made by large language models. This task aims to systematically evaluate the model's output to uncover its limitations and biases in specific scenarios, thereby providing a scientific basis for model optimization. Understanding these errors helps improve the accuracy and reliability of the model, enhancing its performance in real-world applications.