1k citations · 1.4k across the 27 of their papers we have counts for
4 papers · 1 filter
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models
Martin Pawelczyk, Lillian Sun, Zhenting Qi +2
The rapid proliferation of generative AI, especially large language models, has led to their integration into a variety of applications. A key phenomenon known as weak-to-strong ge…
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
Predictive machine learning models are becoming increasingly deployed in high-stakes contexts involving sensitive personal data; in these contexts, there is a trade-off between mod…
Machine Unlearning Fails to Remove Data Poisoning Attacks
Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu +3
We revisit the efficacy of several practical methods for approximate machine unlearning developed for large-scale deep learning. In addition to complying with data deletion request…
Towards Non-Adversarial Algorithmic Recourse
Tobias Leemann, Martin Pawelczyk, Bardh Prenkaj +1
The streams of research on adversarial examples and counterfactual explanations have largely been growing independently. This has led to several recent works trying to elucidate th…