Typicalness-Aware Learning for Improved Failure Detection in Deep Neural Networks

Overfitting on atypical samples with ambiguous content can lead to overconfidence in deep neural networks, hindering failure detection. Typicalness-Aware Learning (TAL) addresses this by dynamically adjusting the optimization of typical and atypical samples, improving the reliability of confidence scores and failure detection.