5 citations · 5 across the 2 of their papers we have counts for
3 papers · 1 filter
Building Fast, Evaluating Slow: Pipeline Choices Dominate Autointerpretability Score Variance
Sinie van der Ben, Neele Roch, Anna Hedström +1
Cross-paper comparison of sparse autoencoder (SAE) interpretability often relies on autointerpretability scores. In this evaluation pipeline, a language model (LM) explains each fe…
CoSy: Evaluating Textual Explanations of Neurons
Laura Kopf, Philine Lou Bommer, Anna Hedström +3
A crucial aspect of understanding the complex nature of Deep Neural Networks (DNNs) is the ability to explain learned concepts within their latent representations. While methods ex…
Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability
Shanghua Liu, Anna Hedström, Deepak Hanike Basavegowda +2
Grasslands are known for their high biodiversity and ability to provide multiple ecosystem services. Challenges in automating the identification of indicator plants are key obstacl…