Near_OOD_with_pre_training (1).pdf

Near out-of-distribution detection (OOD) is a major challenge for deep neural networks. We demonstrate that large-scale pre-trained transformers can significantly improve the state-of-the-art (SOT A) on a range of near OOD tasks across different data modalities.