2 citations · 2 across the 2 of their papers we have counts for
5 papers
CEL: Comprehensive Counterfactual Explanations Library and Benchmark
Oleksii Furman, Łukasz Lenkiewicz, Marcel Musiałek +1
Counterfactual explanations are a prominent approach in explainable artificial intelligence (xAI), providing actionable guidance on what input changes would alter a model's predict…
V4FinBench: Benchmarking Tabular Foundation Models, LLMs, and Standard Methods on Corporate Bankruptcy Prediction
Marcin Kostrzewa, Sebastian Tomczak, Roman Furman +5
Corporate bankruptcy prediction is a high-stakes financial task characterized by severe class imbalance and multi-horizon forecasting demands. Public datasets supporting it remain…
Are Foundation Models Useful for Bankruptcy Prediction?
Marcin Kostrzewa, Oleksii Furman, Roman Furman +2
Foundation models have shown promise across various financial applications, yet their effectiveness for corporate bankruptcy prediction remains systematically unevaluated against e…
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels
Oleksii Furman, Patryk Wielopolski, Łukasz Lenkiewicz +2
The growing complexity of AI systems has intensified the need for transparency through Explainable AI (XAI). Counterfactual explanations (CFs) offer actionable "what-if" scenarios…
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows
Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski +1
We present PPCEF, a novel method for generating probabilistically plausible counterfactual explanations (CFs). PPCEF advances beyond existing methods by combining a probabilistic f…