INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 5/15/2026, 4:00:00 AM · TLP amber
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Privacy Auditing with Zero (0) Training Run arXiv:2605.14591v1 Announce Type: new Abstract: Privacy auditing provides empirical lower bounds on the differential privacy parameters of learning algorithms. Existing methods, however, require interventional access to the training pipeline, either to retrain multiple times or to randomize data inclusion. This is often infeasible for large deployed systems such as foundation models. We introduce Zero-Run privacy auditing, a post-h…
https://arxiv.org/abs/2605.14591
sha256:0d23dfb6ba3c88cac3943cf2413424b2503a410c21e96c68d39eabec9b23645f
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