AI RESEARCH
Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption
arXiv CS.LG
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ArXi:2605.01137v1 Announce Type: new Metric differential privacy (mDP) strengthens local differential privacy (LDP) by scaling noise to semantic distance, but many machine learning (ML) systems are consumed under joint observation, where model-agnostic, per-record guarantees can miss leakage from evidence aggregation. We