Oleksii Furman — accepted AI-conference papers

2026

Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels

Oleksii Furman, Patryk Wielopolski, Łukasz Lenkiewicz, Jerzy Stefanowski, Maciej Zięba

IJCAI 2026

The growing complexity of AI systems has intensified the need for transparency through Explainable AI (XAI). Counterfactual explanations (CFs) offer actionable "what-if" scenarios on three levels: Local CFs providing instance-specific insights, Global CFs addressing broader trends, and Group-wise CF

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2025

DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control

Oleksii Furman, Ulvi Movsum-zada, Patryk Marszałek, Maciej Zieba, Marek Śmieja

NeurIPS 2025poster

Counterfactual explanations play a pivotal role in explainable artificial intelligence (XAI) by offering intuitive, human-understandable alternatives that elucidate machine learning model decisions. Despite their significance, existing methods for generating counterfactuals often require constant ac…

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