Unsupervised Symbolic Music Segmentation using Ensemble Temporal Prediction Errors. - Shahaf Bassan; Yossi Adi; Jeffrey S. Rosenschein (INTERSPEECH, 2022)

Towards Formal Approximated Minimal Explanations of Neural Networks. - Shahaf Bassan; Guy Katz (CoRR, 2022)

Formally Explaining Neural Networks within Reactive Systems. - Shahaf Bassan; Guy Amir; Davide Corsi; Idan Refaeli; Guy Katz (FMCAD, 2023)

Towards Formal XAI: Formally Approximate Minimal Explanations of Neural Networks. - Shahaf Bassan; Guy Katz (TACAS (1), 2023)

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. - Haoze Wu 001; Omri Isac; Aleksandar Zeljic; Teruhiro Tagomori; Matthew L. Daggitt; Wen Kokke; Idan Refaeli; Guy Amir; Kyle Julian; Shahaf Bassan; Pei Huang 002; Ori Lahav 002; et al. (CAV (2), 2024)

Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation. - Guy Amir; Shahaf Bassan; Guy Katz (ECAI, 2024)

Local vs. Global Interpretability: A Computational Complexity Perspective. - Shahaf Bassan; Guy Amir; Guy Katz (ICML, 2024)

On the Computational Tractability of the (Many) Shapley Values. - Reda Marzouk; Shahaf Bassan; Guy Katz; Colin de la Higuera (AISTATS, 2025)

Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons. - Shahaf Bassan; Ron Eliav; Shlomit Gur (ICLR, 2025)

Self-Explaining Neural Networks for Business Process Monitoring. - Shahaf Bassan; Shlomit Gur; Sergey Zeltyn; Konstantinos Mavrogiorgos; Ron Eliav; Dimosthenis Kyriazis (CoRR, 2025)

CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection. - Ron Eliav; Arie Cattan; Eran Hirsch; Shahaf Bassan; Elias Stengel-Eskin; Mohit Bansal; Ido Dagan (CoRR, 2025)

What makes an Ensemble (Un) Interpretable? - Shahaf Bassan; Guy Amir; Meirav Zehavi; Guy Katz (CoRR, 2025)

Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations. - Shahaf Bassan; Yizhak Yisrael Elboher; Tobias Ladner; Matthias Althoff; Guy Katz (CoRR, 2025)