Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling. - Tobias Leemann; Moritz Sackmann; Jörn Thielecke; Ulrich Hofmann 002 (ESANN, 2021)

Multi-Step Training for Predicting Roundabout Traffic Situations. - Moritz Sackmann; Tobias Leemann; Henrik Bey; Ulrich Hofmann 002; Jörn Thielecke (ITSC, 2021)

A Consistent and Efficient Evaluation Strategy for Attribution Methods. - Yao Rong; Tobias Leemann; Vadim Borisov; Gjergji Kasneci; Enkelejda Kasneci (ICML, 2022)

Evaluating Feature Attribution: An Information-Theoretic Perspective. - Yao Rong; Tobias Leemann; Vadim Borisov; Gjergji Kasneci; Enkelejda Kasneci (CoRR, 2022)

Disentangling Embedding Spaces with Minimal Distributional Assumptions. - Tobias Leemann; Michael Kirchhof; Yao Rong; Enkelejda Kasneci; Gjergji Kasneci (CoRR, 2022)

Towards Human-centered Explainable AI: User Studies for Model Explanations. - Yao Rong; Tobias Leemann; Thai-trang Nguyen; Lisa Fiedler; Tina Seidel; Gjergji Kasneci; Enkelejda Kasneci (CoRR, 2022)

I Prefer not to Say: Operationalizing Fair and User-guided Data Minimization. - Tobias Leemann; Martin Pawelczyk; Christian Thomas Eberle; Gjergji Kasneci (CoRR, 2022)

Language Models are Realistic Tabular Data Generators. - Vadim Borisov; Kathrin Seßler; Tobias Leemann; Martin Pawelczyk; Gjergji Kasneci (ICLR, 2023)

On the Trade-Off between Actionable Explanations and the Right to be Forgotten. - Martin Pawelczyk; Tobias Leemann; Asia Biega; Gjergji Kasneci (ICLR, 2023)

Gaussian Membership Inference Privacy. - Tobias Leemann; Martin Pawelczyk; Gjergji Kasneci (NeurIPS, 2023)

Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes. - Bardh Prenkaj; Mario Villaizán-Vallelado; Tobias Leemann; Gjergji Kasneci (PKDD/ECML Workshops (1), 2023)

When are post-hoc conceptual explanations identifiable? - Tobias Leemann; Michael Kirchhof; Yao Rong; Enkelejda Kasneci; Gjergji Kasneci (UAI, 2023)

I Prefer Not to Say: Protecting User Consent in Models with Optional Personal Data. - Tobias Leemann; Martin Pawelczyk; Christian Thomas Eberle; Gjergji Kasneci (AAAI, 2024)

The Language of Trauma: Modeling Traumatic Event Descriptions Across Domains with Explainable AI. - Miriam Schirmer; Tobias Leemann; Gjergji Kasneci; Jürgen Pfeffer; David Jurgens (EMNLP (Findings), 2024)

Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals. - Bardh Prenkaj; Mario Villaizán-Vallelado; Tobias Leemann; Gjergji Kasneci (KDD, 2024)

Towards Non-adversarial Algorithmic Recourse. - Tobias Leemann; Martin Pawelczyk; Bardh Prenkaj; Gjergji Kasneci (xAI (3), 2024)

Towards Human-Centered Explainable AI: A Survey of User Studies for Model Explanations. - Yao Rong; Tobias Leemann; Thai-trang Nguyen; Lisa Fiedler; Peizhu Qian; Vaibhav V. Unhelkar; Tina Seidel; Gjergji Kasneci; Enkelejda Kasneci (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Deep Neural Networks and Tabular Data: A Survey. - Vadim Borisov; Tobias Leemann; Kathrin Seßler; Johannes Haug; Martin Pawelczyk; Gjergji Kasneci (IEEE Trans. Neural Networks Learn. Syst., 2024)

Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation. - Tobias Leemann; Periklis Petridis; Giuseppe Vietri; Dionysis Manousakas; Aaron Roth 001; Sergül Aydöre (ICLR, 2025)

Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers. - Tobias Leemann; Alina Fastowski; Felix Pfeiffer; Gjergji Kasneci (Trans. Mach. Learn. Res., 2025)