Auditing: Active Learning with Outcome-Dependent Query Costs
(NIPS) Learns from a binary classifier paying only for negative labels.
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- 2026-10-10
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Auditing Fairness by Betting arxiv.org
(Neurips) [Code] Sequential methods that allows for the continuous monitoring of incoming data from a black-box classifier or regressor.
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Auditing Algorithms: On Lessons Learned and the Risks of DataMinimization dl.acm.org
(AIES) A practical audit for a well-being recommendation app developed by Telefónica (mostly on bias).
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Privacy Auditing with One (1) Training Run neurips.cc
(NeurIPS - best paper) A scheme for auditing differentially private machine learning systems with a single training run.
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CALM: Curiosity-Driven Auditing for Large Language Models arxiv.org
(AAAI) Auditing as a black-box optimization problem where the goal is to automatically uncover input-output pairs of the target LLMs that exhibit illegal, immoral, or unsafe behaviors.
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Adversarial Learning dl.acm.org
(KDD) Reverse engineering of remote linear classifiers, using membership queries.
Audit Algorithms › Papers > 2013: “(NIPS) Learns from a binary classifier paying only for negative labels.”