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cs.AI2026
Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
Georgii Mikriukov, Grégoire Montavon, Marina M. -C. Höhne
Post-hoc explanation methods are widely used to interpret black-box predictions, but their generation is often computationally expensive and their reliability is not guaranteed. We…
cs.AI2024★ 1 cited
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation
Kristoffer Wickstrøm, Marina Marie-Claire Höhne, Anna Hedström
The lack of ground truth explanation labels is a fundamental challenge for quantitative evaluation in explainable artificial intelligence (XAI). This challenge becomes especially p…