Ahyoung Oh

Sparsity as a Key: Unlocking New Insights from Latent Structures for Out-of-Distribution Detection

Sparse Autoencoders (SAEs) have demonstrated significant success in interpreting Large Language Models (LLMs) by decomposing dense representations into sparse, semantic components. However, their potential for analyzing Vision Transformers (ViTs) remains largely under-explored. In this work, we pres