collaborators

5 papers

cs.LG2026

Proxy-Based Approximation of Shapley and Banzhaf Interactions

Santo M. A. R. Thies, Hubert Baniecki, R. Teal Witter +3

Shapley and Banzhaf interactions capture the complex dynamics inherent in modern machine learning applications. However, current estimators for these higher-order interactions trad…

cs.CV2026

SwordBench: Evaluating Orthogonality of Steering Image Representations

Vladimir Zaigrajew, Dawid Pludowski, Hubert Baniecki +1

Steering or intervening on model representations at inference time to correct predictions is essential for AI interpretability and safety, yet existing evaluation protocols are lim…

stat.ML2026

Functional Decomposition and Shapley Interactions for Interpreting Survival Models

Sophie Hanna Langbein, Hubert Baniecki, Fabian Fumagalli +3

Hazard and survival functions are natural, interpretable targets in time-to-event prediction, but their inherent non-additivity fundamentally limits standard additive explanation m…

cs.CV2025

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions

Hubert Baniecki, Maximilian Muschalik, Fabian Fumagalli +3

Language-image pre-training (LIP) enables the development of vision-language models capable of zero-shot classification, localization, multimodal retrieval, and semantic understand…

cs.LG2025

Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning

Hubert Baniecki, Przemyslaw Biecek

A common belief is that intrinsically interpretable deep learning models ensure a correct, intuitive understanding of their behavior and offer greater robustness against accidental…