Pawelczyk, Martin

16 publications

NeurIPS 2025 Efficiently Verifiable Proofs of Data Attribution Ari Karchmer, Seth Neel, Martin Pawelczyk

ICLR 2025 Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu, Gautam Kamath, Ayush Sekhari, Seth Neel

ICMLW 2024 Explaining the Model, Protecting Your Data: Revealing and Mitigating the Data Privacy Risks of Post-Hoc Model Explanations via Membership Inference Catherine Huang, Martin Pawelczyk, Himabindu Lakkaraju

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

ICML 2024 In-Context Unlearning: Language Models as Few-Shot Unlearners Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju

ICMLW 2024 On the Privacy Risks of Post-Hoc Explanations of Foundation Models Catherine Huang, Martin Pawelczyk, Himabindu Lakkaraju

NeurIPS 2023 Gaussian Membership Inference Privacy Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci

ICLR 2023 Language Models Are Realistic Tabular Data Generators Vadim Borisov, Kathrin Sessler, Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci

AISTATS 2023 On the Privacy Risks of Algorithmic Recourse Martin Pawelczyk, Himabindu Lakkaraju, Seth Neel

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 Probabilistically Robust Recourse: Navigating the Trade-Offs Between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk, Teresa Datta, Johan Van den Heuvel, Gjergji Kasneci, Himabindu Lakkaraju

AISTATS 2022 Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju

NeurIPSW 2022 On the Trade-Off Between Actionable Explanations and the Right to Be Forgotten Martin Pawelczyk, Tobias Leemann, Asia Biega, Gjergji Kasneci

NeurIPS 2022 OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju

ICLRW 2022 Rethinking Stability for Attribution-Based Explanations Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju

UAI 2020 On Counterfactual Explanations Under Predictive Multiplicity Martin Pawelczyk, Klaus Broelemann, Gjergji. Kasneci