5 citations · 5 across the 2 of their papers we have counts for
4 papers
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…
Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test
Anna Hedström, Leander Weber, Sebastian Lapuschkin +1
The Model Parameter Randomisation Test (MPRT) is widely acknowledged in the eXplainable Artificial Intelligence (XAI) community for its well-motivated evaluative principle: that th…
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…