Get started
Author

Martin Pawelczyk

Observed name: Pawelczyk, Martin
ORCID: 0000-0002-6191-4434
Observed ORCID: 0000-0002-6191-4434
OpenAlex ID: A5044448837
Deep Neural Networks and Tabular Data: A Survey
2022 · Vadim Borisov, Tobias Leemann, et al. · IEEE Transactions on Neural Networks and Learning Systems · 1,090
Learning Model-Agnostic Counterfactual Explanations for Tabular Data
2020 · Martin Pawelczyk, Klaus Broelemann, et al. · International World Wide Web Conference (WWW) · 167
OpenXAI: Towards a Transparent Evaluation of Model Explanations
2022 · Chirag Agarwal, Satyapriya Krishna, et al. · neural information processing systems · 115
PDF
Language Models are Realistic Tabular Data Generators
2022 · Borisov, Vadim, Seßler, Kathrin, et al. · arXiv (Cornell University) · 68
PDF
On Counterfactual Explanations under Predictive Multiplicity
2020 · Pawelczyk, Martin, Broelemann, Klaus, et al. · arXiv (Cornell University) · 43
PDF
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
2021 · Pawelczyk, Martin, Bielawski, Sascha, et al. · arXiv (Cornell University) · 36
PDF
Rethinking Stability for Attribution-based Explanations
2022 · Agarwal, Chirag, Johnson, Nari, et al. · arXiv (Cornell University) · 27
PDF
Linking Aid to the Sustainable Development Goals – a machine learning approach
2019 · Arnaud Pincet, Shu Okabe, et al. · OECD development co-operation working papers · 21
In-Context Unlearning: Language Models as Few Shot Unlearners
2023 · Pawelczyk, Martin, Neel, Seth, et al. · arXiv (Cornell University) · 20
PDF
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
2022 · Pawelczyk, Martin, Datta, Teresa, et al. · arXiv (Cornell University) · 16
PDF
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis
2021 · Pawelczyk, Martin, Agarwal, Chirag, et al. · arXiv (Cornell University) · 15
PDF
On the Privacy Risks of Algorithmic Recourse
2022 · Pawelczyk, Martin, Lakkaraju, Himabindu, et al. · arXiv (Cornell University) · 7
PDF
Towards User Empowerment.
2019 · Martin Pawelczyk, Johannes Haug, et al. · arXiv (Cornell University) · 6
On the Connections between Counterfactual Explanations and Adversarial Examples.
2021 · Martin Pawelczyk, Shalmali Joshi, et al. · arXiv (Cornell University) · 5
On the Trade-Off between Actionable Explanations and the Right to be Forgotten
2022 · Pawelczyk, Martin, Leemann, Tobias, et al. · arXiv (Cornell University) · 4
PDF
Towards Non-adversarial Algorithmic Recourse
2024 · Tobias Leemann, Martin Pawelczyk, et al. · Communications in computer and information science · 3
PDF
I Prefer Not to Say: Protecting User Consent in Models with Optional Personal Data
2024 · Tobias Leemann, Martin Pawelczyk, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 1
PDF
Gaussian Membership Inference Privacy
2023 · Tobias Leemann, Martin Pawelczyk, et al. · neural information processing systems · 1
PDF
Model Selection in Local Approximation Gaussian Processes: A Markov Random Fields Approach
2021 · Hamed Jalali, Martin Pawelczyk, et al. · IEEE International Conference on Big Data (BigData) · 1
PDF
LinMix: Data Mixing as Linear Domain Attribution
2026 · Baniecki, Hubert, Biecek, Przemyslaw, et al. · arXiv (Cornell University)
PDF
Don't Trust Stubborn Neighbors: A Security Framework for Agentic Networks
2026 · Abedini, Samira, Mavali, Sina, et al. · CISPA Helmholtz Center
Multi-Agent Systems are Mixtures of Experts: Who Becomes an Influencer?
2026 · Bause, Franka, Niederle, Jonas, et al. · CISPA Helmholtz Center
Validity Threats for Foundation Model Research
2026 · König, Gunnar, Pawelczyk, Martin, et al. · arXiv (Cornell University)
PDF
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models
2026 · Association for Computational Linguistics 2026, Kumar, Aounon, et al. · Underline Science Inc.
Multi-Agent Systems are Mixtures of Experts: Who Becomes an Influencer?
2026 · Bause, Franka, Niederle, Jonas, et al. · arXiv (Cornell University)
PDF
Works count: 41
Citation count: 1,646
H-index: 11
I10-index: 11
Year
Topic
Type