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20222026
most citedScientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena

28 citations · 42 across the 6 of their papers we have counts for

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cs.LG2026

We Need Explanation Cards to Connect Explanation Algorithms to the Real World

Eric Günther, Balázs Szabados, Kristof Meding +3

Algorithmic explanations are intended to help stakeholders understand opaque algorithmic decisions, but in practice, they often fall short. First, the meaning of algorithmic explan…

stat.ML2026

Explainable AI Isn't Enough! Rethinking Algorithmic Contestability

Timo Freiesleben, Kristof Meding, Gunnar König

Machine learning systems increasingly make life-changing decisions about individuals, such as loan approvals, hiring, and cheating detection, raising a pressing question: how can i…