With the rapid advancement in the performance of deep neural networks (DNNs), there has
been significant interest in deploying and incorporating artificial intelligence (AI) systems …

Abstract Language Models for text classification often produce overconfident predictions for
both in-distribution and out-of-distribution samples, ie, the model's output probabilities do not …

Trustworthy prediction in Deep Neural Networks (DNNs), including Pre-trained Language
Models (PLMs) is important for safety-critical applications in the real world. However, DNNs …

Model calibration aims to align confidence with prediction correctness. The Cross-Entropy
CE) loss is widely used for calibrator training, which enforces the model to increase …

Unsupervised domain adaptation (UDA) has seen significant efforts to enhance model
accuracy for an unlabeled target domain with the help of one or more labeled source …

抄録 深層学習モデルの予測の信頼性が高いことは, 実世界で高い安全性が必要とされる領域で
応用するために重要である. しかし, 深層学習モデルには実際の正解率と予測された信頼度の乖離 …