works on
interpretability 1neural networks 1out-of-distribution detection 1representation learning 1sparse autoencoders 1

From the 1 of 1 linked paper with an AI index.

collaborators

1 paper

cs.LG2026

Sparse Autoencoders for Interpretable Out-of-Distribution Detection

Ayush Karmacharya, Luke Luschwitz, Lucia Romero +2

The paper proposes using sparse autoencoders to extract interpretable sparse features from intermediate neural network layers and defines an OOD detection score based on cosine sim…