1 citations · 2 across the 4 of their papers we have counts for
4 papers
Does Explanation Correctness Matter? Linking Computational XAI Evaluation to Human Understanding
Gregor Baer, Chao Zhang, Isel Grau +1
Explainable AI (XAI) methods are commonly evaluated using functional correctness metrics, sometimes termed faithfulness or fidelity, which estimate how closely an explanation refle…
Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust
Mohsen Abbaspour Onari, Lucie Charlotte Magister, Yaoxin Wu +10
Distal myopathy represents a genetically heterogeneous group of skeletal muscle disorders with broad clinical manifestations, posing diagnostic challenges in radiology. To address…
Why Do Class-Dependent Evaluation Effects Occur with Time Series Feature Attributions? A Synthetic Data Investigation
Gregor Baer, Isel Grau, Chao Zhang +1
Evaluating feature attribution methods represents a critical challenge in explainable AI (XAI), as researchers typically rely on perturbation-based metrics when ground truth is una…
Class-Dependent Perturbation Effects in Evaluating Time Series Attributions
Gregor Baer, Isel Grau, Chao Zhang +1
As machine learning models become increasingly prevalent in time series applications, Explainable Artificial Intelligence (XAI) methods are essential for understanding their predic…