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cs.AI2025
Ensuring Medical AI Safety: Interpretability-Driven Detection and Mitigation of Spurious Model Behavior and Associated Data
Frederik Pahde, Thomas Wiegand, Sebastian Lapuschkin +1
Deep neural networks are increasingly employed in high-stakes medical applications, despite their tendency for shortcut learning in the presence of spurious correlations, which can…
cs.AI2024
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers
Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Reduan Achtibat +3
To solve ever more complex problems, Deep Neural Networks are scaled to billions of parameters, leading to huge computational costs. An effective approach to reduce computational r…