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Dominik Geißler

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Preprint Sep 2026

Don't Blame the Model, Verify the Data: An Evaluation of SMT-based Dataset Verification (Extended Version)

The EU AI Act mandates that datasets for high-risk machine learning (ML) systems meet strict quality criteria such as soundness and bias mitigation. While Satisfiability Modulo Theory (SMT) solving offers a formal approach to verifying these properties, its scalability in realistic ML settings remains unexplored. To br...

Sehee Park, Dominik Geißler, A. Aleksandrov et al. · 0 citations

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