FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

Excerpt

arXiv:2610.08537v1 Announce Type: new Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would lead to a more favourable outcome. To be useful in practice, such an explanation should change few features and change them as little as possible, properties known as sparsity and proximity. We observe that existing methods remain limited in this respect, especially for numerical features, whether the