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Assessing Per-Sample Membership Inference Vulnerability without Retraining
Per-sample membership inference vulnerability is governed by a data-dependent geometric measure, yielding a surrogate score using only a single model that outperforms loss-based baselines at identifying high-risk training points.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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