Auditing Local Explanations is Hard
(NeurIPS) Gives the (prohibitive) query complexity of auditing explanations.
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- 2026-10-10
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XAudit : A Theoretical Look at Auditing with Explanations arxiv.org
(Arxiv) Formalizes the role of explanations in auditing and investigates if and how model explanations can help audits.
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Remote Explainability faces the bouncer problem rdcu.be
(Nature Machine Intelligence volume 2, pages529–539) (Code) Shows the impossibility (with one request) or the difficulty to spot lies on the explanations of a remote AI decision.
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Under manipulations, are some AI models harder to audit? grodino.github.io
(SATML) Relates the difficulty of black-box audits to the capacity of the targeted models, using the Rademacher complexity.
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Auditing Fairness by Betting arxiv.org
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Auditing fairness under unawareness through counterfactual reasoning sciencedirect.com
(Information Processing & Management) Shows how to unveil whether a black-box model, complying with the regulations, is still biased or not.
Audit Algorithms › Papers > 2024: “(NeurIPS) Gives the (prohibitive) query complexity of auditing explanations.”