2 papers
cs.LG2026
Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection
Gianluca Guglielmo, Marc Masana
State-of-the-art post-hoc out-of-distribution detection methods rely on intermediate layer activation editing. However, they exhibit inconsistent performance across datasets and mo…
cs.LG2025
Leveraging Intermediate Representations for Better Out-of-Distribution Detection
Gianluca Guglielmo, Marc Masana
In real-world applications, machine learning models must reliably detect Out-of-Distribution (OoD) samples to prevent unsafe decisions. Current OoD detection methods often rely on…