With the increasing demand for understanding the decision-making processes of artificial intelligence applications, explainable AI (XAI) systems have become increasingly important. Counterfactual explana- tions, a promising ...

In eXplainable Artificial Intelligence (XAI), instance-based explanations have gained importance as a method for illuminating complex models by highlighting differences or similarities between the samples and their ...

Post-hoc explanation systems offer valuable insights to increase understanding of the predictions made by black-box models. Counterfactual explanations, an instance-based post-hoc explanation method, aim to demonstrate how ...