arxiv
PublishedJuly 15, 2026 at 4:00 AM
—neutral
Sparse Autoencoders for Interpretable Out-of-Distribution Detection
Publisher summary· verbatim
arXiv:2607.12094v1 Announce Type: cross Abstract: Reliable detection of out-of-distribution (OOD) samples is crucial for the safe deployment of machine learning models. Neural networks often produce overconfident predictions for inputs that deviate from their training data, leading to significant de
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Originally published on arxiv ↗