New framework for auditing machine unlearning

Google Research introduces Regularized f-Divergence Kernel Tests, a new framework for auditing machine unlearning that uses statistical divergence measures to verify whether a model has forgotten specific data, presented at AISTATS 2026.

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We introduce Regularized f-Divergence Kernel Tests, presented at AISTATS 2026, a new framework designed to make auditing ML models much more sensitive, flexible, and accurate.
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Announced: 10 Jun 2026 17:34 UTC
Detected: 03 Aug 2026 21:12 UTC (+54d after)

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