Alexander Koebler — accepted AI-conference papers

2026

LVLM-Aided Alignment of Task-Specific Vision Models

Alexander Koebler, Lukas Kuhn, Ingo Thon, Florian Buettner

CVPR 2026

In high-stakes domains, small task-specific vision models are crucial due to their low computational requirements and the availability of numerous methods to explain their results. However, these explanations often reveal that the models do not align well with human domain knowledge, relying instead

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2025

Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention

Alexander Koebler, Thomas Decker, Ingo Thon, Volker Tresp, Florian Buettner

AISTATS 2025poster

We study the problem of monitoring machine learning models under gradual distribution shifts, where circumstances change slowly over time, often leading to unnoticed yet significant declines in accuracy. To address this, we propose Incremental Uncertainty-aware Performance Monitoring (IUPM), a novel…

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