3 papers
cs.LG2026
Reproducibility study on how to find Spurious Correlations, Shortcut Learning, Clever Hans or Group-Distributional non-robustness and how to fix them
Ole Delzer, Sidney Bender
Deep Neural Networks (DNNs) are increasingly utilized in high-stakes domains like medical diagnostics and autonomous driving where model reliability is critical. However, the resea…
cs.LG2026
SCE-LITE-HQ: Smooth visual counterfactual explanations with generative foundation models
Ahmed Zeid, Sidney Bender
Modern neural networks achieve strong performance but remain difficult to interpret in high-dimensional visual domains. Counterfactual explanations (CFEs) provide a principled appr…
cs.AI2023
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation
Sidney Bender, Christopher J. Anders, Pattarawatt Chormai +3
This paper introduces a novel technique called counterfactual knowledge distillation (CFKD) to detect and remove reliance on confounders in deep learning models with the help of hu…