Anna Hedström

According to our database, Anna Hedström authored at least 15 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework.

Laura Kopf, Nils Feldhus, Kirill Bykov, Philine Lou Bommer, Anna Hedström, Marina M.-C. Höhne, Oliver Eberle

CoRR, June, 2025

Evaluating Interpretable Methods via Geometric Alignment of Functional Distortions.

Anna Hedström, Philine Lou Bommer, Thomas F. Burns, Sebastian Lapuschkin, Wojciech Samek, Marina M.-C. Höhne

Trans. Mach. Learn. Res., 2025

Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution.

Carlos Eiras-Franco, Anna Hedström, Marina M.-C. Höhne

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Benchmarking XAI Explanations with Human-Aligned Evaluations.

Rémi Kazmierczak, Steve Azzolin, Eloïse Berthier, Anna Hedström, Patricia Delhomme, Nicolas Bousquet, Goran Frehse, Massimiliano Mancini, Baptiste Caramiaux, Andrea Passerini, Gianni Franchi

CoRR, 2024

Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond.

Dilyara Bareeva, Galip Ümit Yolcu, Anna Hedström, Niklas Schmolenski, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2024

Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test.

Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne

CoRR, 2024

A Fresh Look at Sanity Checks for Saliency Maps.

Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne

Proceedings of the Explainable Artificial Intelligence, 2024

CoSy: Evaluating Textual Explanations of Neurons.

Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Explainable AI in grassland monitoring: Enhancing model performance and domain adaptability.

Shanghua Liu, Anna Hedström, Deepak Hanike Basavegowda, Cornelia Weltzien, Marina M.-C. Höhne

Proceedings of the 44. GIL-Jahrestagung, Informatik in der Land-, Forst- und Ernährungswirtschaft, 2024

From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation.

Kristoffer Wickstrøm, Marina M.-C. Höhne, Anna Hedström

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus.

Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

Trans. Mach. Learn. Res., 2023

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond.

Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

J. Mach. Learn. Res., 2023

Finding the right XAI method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science.

Philine Lou Bommer, Marlene Kretschmer, Anna Hedström, Dilyara Bareeva, Marina M.-C. Höhne

CoRR, 2023

2022

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations.

Anna Hedström, Leander Weber, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

CoRR, 2022

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights.

Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022