leakage

MosaicLeaks introduces a new benchmark for measuring privacy leakage in deep-research AI agents, showing that agents often leak private information through external queries and proposing a training method (PA-DR) to reduce leakage while improving task performance.

Introduces MosaicLeaks, a benchmark of 1,001 multi-hop deep research tasks that chain private enterprise documents with public web queries to evaluate privacy leakage. Finds that models leak sensitive information at multiple levels, and proposes PA-DR, a reinforcement learning framework that reduces leakage while improving task accuracy.