2024
Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations
UAI 2024poster
Detecting out-of-distribution (OOD) instances is crucial for the reliable deployment of machine learning models in real-world scenarios. OOD inputs are commonly expected to cause a more uncertain prediction in the primary task; however, there are OOD cases for which the model returns a highly confid…