Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection

Researchers propose Ranked Activation Shift, a hyperparameter-free post-hoc method for detecting out-of-distribution inputs in neural networks. The method addresses instability in existing activation-based detection approaches by using a fixed in-distribution reference profile instead of scaled activation magnitudes, showing consistent performance across datasets and architectures.