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cs.GT2026
Differentially Private Auditing Under Strategic Response
Florian A. D. Burnat
Regulatory audits of AI systems increasingly rely on differential privacy (DP) to protect training data and model internals. We study audit design when the audited developer can st…
cs.GT2026
Quotient Semivalues for False-Name-Resistant Data Attribution
Florian A. D. Burnat, Brittany I. Davidson
Data valuation methods allocate payments and audit training data's contribution to machine-learning pipelines; however, they often assume passive contributors. In reality, contribu…