1 citations · 1 across the 4 of their papers we have counts for
4 papers
Conditioned Activation Transport for T2I Safety Steering
Maciej Chrabąszcz, Aleksander Szymczyk, Jan Dubiński +3
Despite their impressive capabilities, current Text-to-Image (T2I) models remain prone to generating unsafe and toxic content. While activation steering offers a promising inferenc…
Controlled privacy leakage propagation throughout overlapping grouped learning
Shahrzad Kiani, Franziska Boenisch, Stark C. Draper
Federated Learning (FL) is the standard protocol for collaborative learning. In FL, multiple workers jointly train a shared model. They exchange model updates calculated on their d…
Differentially Private Federated Learning With Time-Adaptive Privacy Spending
Shahrzad Kiani, Nupur Kulkarni, Adam Dziedzic +2
Federated learning (FL) with differential privacy (DP) provides a framework for collaborative machine learning, enabling clients to train a shared model while adhering to strict pr…
A Unified Framework for Quantifying Privacy Risk in Synthetic Data
Matteo Giomi, Franziska Boenisch, Christoph Wehmeyer +1
Synthetic data is often presented as a method for sharing sensitive information in a privacy-preserving manner by reproducing the global statistical properties of the original data…