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cs.AI2026
U-CECE: A Universal Multi-Resolution Framework for Conceptual Counterfactual Explanations
Angeliki Dimitriou, Nikolaos Chaidos, Maria Lymperaiou +2
As AI models grow more complex, explainability is essential for building trust, yet concept-based counterfactual methods still face a trade-off between expressivity and efficiency.…
cs.AI2023
Choose your Data Wisely: A Framework for Semantic Counterfactuals
Edmund Dervakos, Konstantinos Thomas, Giorgos Filandrianos +1
Counterfactual explanations have been argued to be one of the most intuitive forms of explanation. They are typically defined as a minimal set of edits on a given data sample that,…