2 papers
cs.LG2026
Mastering the Minority: An Uncertainty-guided Multi-Expert Framework for Challenging-tailed Sequence Learning
Ye Wang, Zixuan Wu, Lifeng Shen +4
Imbalanced data distribution remains a critical challenge in sequential learning, leading models to easily recognize frequent categories while failing to detect minority classes ad…
cs.CV2024
Typicalness-Aware Learning for Failure Detection
Yijun Liu, Jiequan Cui, Zhuotao Tian +4
Deep neural networks (DNNs) often suffer from the overconfidence issue, where incorrect predictions are made with high confidence scores, hindering the applications in critical sys…