On the Theoretical Limits of Out-of-Distribution Detection

The core message of this paper is to investigate the theoretical limits of learnability for out-of-distribution (OOD) detection under risk and AUC metrics. The authors discover necessary and sufficient conditions for the learnability of OOD detection in several representative domain spaces, revealing the challenges and possibilities of successful OOD detection in practice.