outlier exposure (OE) is powerful in out-of-distribution (OOD) detection,
enhancing detection capability via model fine-tuning with surrogate OOD data.
However, surrogate data typically deviate from test OOD data. Thus, the
performance of OE, when facing unseen OOD data, can be weakene