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Yuchen Tian, Kaixin Li, Hao Chen, Ziyang Luo, Hongzhan Lin, Sebastian Schelter, Lun Du, Jing Ma
AmbiGraph-Eval: Can LLMs Effectively Handle Ambiguous Graph Queries?
Oliver Eberle, Thomas McGee, Hamza Giaffar, Taylor Webb, Ida Momennejad
How do LLMs Solve Multi-step Reasoning? An Algorithmic Evaluation
Frederik Pahde, Thomas Wiegand, Sebastian Lapuschkin & Wojciech Samek
Ensuring medical AI safety: interpretability-driven detection and mitigation of spurious model behavior and associated data
Maximilian Kromer, Panagiotis Agrafiotis, Begüm Demir
Sea-Undistort: A Dataset for Through-Water Image Restoration in High Resolution Airborne Bathymetric Mapping
Barış Büyüktaş, Jonas Klotz, Begüm Demir
FedX: Explanation-Guided Pruning for Communication-Efficient Federated Learning in Remote Sensing
Andrea M. Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Wojciech Samek, Pål Halvorsen, Thomas de Lange, Yuichi Mori, Alexander Hann, Tyler M. Berzin et al.
Exploring the clinical value of concept-based AI explanations in gastrointestinal disease detection
Patrick Wilhelm, Inese Yilmaz, Odej Kao
Noise-Aware Client Selection for Carbon-Efficient Federated Learning via Gradient Norm Thresholding
Simon Baur, Wojciech Samek, Jackie Ma
Benchmarking Uncertainty and its Disentanglement in multi-label Chest X-Ray Classification
Florian Bley, Jacob Kauffmann, Simon León Krug, Klaus-Robert Müller, Grégoire Montavon
Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures
Marco Morik, Ali Hashemi, Klaus-Robert Muller, Stefan Haufe, Shinichi Nakajima