5 papers
On Complexity of Gaussian Sampling
Huanjian Zhou, Taiji Suzuki
We study the number of exact matrix-vector queries needed to sample a centered -dimensional Gaussian with condition number at most to total variation error . Th…
Loose Lips: Understanding Privacy Leakage in Agentic Dialogue
Soumya Sharma, Ayana Hussain, Heber Hwang Arcolezi +4
As LLM agents are increasingly deployed in high-stakes enterprise settings, understanding how they handle sensitive information in agentic dialogue has become critical. Privacy lea…
PrivacySkills: How Privacy Guidance Shapes Source Selection in LLM Agents
Lucas Biechy, Cédric Eichler, Héber H. Arcolezi +1
While prior work has documented privacy failures in LLM agents, it remains unclear how the presentation of privacy guidance influences their choice of information sources. We intro…
IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts
Ayana Hussain, Soumya Sharma, Golnoosh Farnadi +3
Large language models (LLMs) are becoming widely deployed as personal AI assistants with access to sensitive user data, making privacy a major challenge for their design and evalua…
Quantifying the Privacy of Counterfactuals by Leveraging Membership Inference Attacks Against Synthetic Data
Maryam Babaei, Yingke Wang, Hadrien Lautraite +3
Counterfactuals are typically used in high-stakes decision areas to explain a machine learning model by showing how changes to the user profiles result in the desired outcome. Howe…