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Nijat Mehdiyev

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#artificial intelligence Review Oct 2026

Machine learning for journal entry testing: A type-aware evaluation of anomaly detectors under a review budget

Journal entry anomaly detectors are commonly evaluated on the full population with ROC-AUC, precision and recall, ignoring the review budget and which anomaly types are found. We propose a type-aware evaluation combining per-type recall, fair-share type recall (FSR), which caps each type's credit at its budget share, t...

Jan Gronewald, Michel Scherer, Nijat Mehdiyev · 0 citations
Preprint Jul 2026

Improving LLM-Generated Process Model Quality Through Reinforcement Learning: The Role of Reward Function Design

It is demonstrated that reward composition is a primary determinant of optimization outcomes, with effects as large as the decision to apply RL itself, and generalize to any structured generation task where quality is assessed along multiple automated dimensions.

Alexander Rombach, Chantale Lauer, Nijat Mehdiyev · 0 citations

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