17 citations · 21 across the 14 of their papers we have counts for
7 papers · 1 filter
Inadvertent Context Leakage in Language Models
Jaiden Fairoze, Neal Mangaokar, Kamalika Chaudhuri +2
For AI agents to be useful beyond simple chat, they must hold sensitive user context such as calendars, credentials, health records, and financial data. We study whether the mere p…
Learning to Reason in 13 Parameters
John X. Morris, Niloofar Mireshghallah, Mark Ibrahim +1
Recent research has shown that language models can learn to \textit{reason}, often via reinforcement learning. Some work even trains low-rank parameterizations for reasoning, but c…
Privacy Blur: Quantifying Privacy and Utility for Image Data Release
Saeed Mahloujifar, Narine Kokhlikyan, Chuan Guo +1
Image data collected in the wild often contains private information such as faces and license plates, and responsible data release must ensure that this information stays hidden. A…
Observational Auditing of Label Privacy
Iden Kalemaj, Luca Melis, Maxime Boucher +2
Differential privacy (DP) auditing is essential for evaluating privacy guarantees in machine learning systems. Existing auditing methods, however, pose a significant challenge for…
Z0-Inf: Zeroth Order Approximation for Data Influence
Narine Kokhlikyan, Kamalika Chaudhuri, Saeed Mahloujifar
A critical aspect of analyzing and improving modern machine learning systems lies in understanding how individual training examples influence a model's predictive behavior. Estimat…
Auditing -Differential Privacy in One Run
Saeed Mahloujifar, Luca Melis, Kamalika Chaudhuri
Empirical auditing has emerged as a means of catching some of the flaws in the implementation of privacy-preserving algorithms. Existing auditing mechanisms, however, are either co…
Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds
Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten +2
Protecting privacy during inference with deep neural networks is possible by adding noise to the activations in the last layers prior to the final classifiers or other task-specifi…