Lukas Kuhn — 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

Efficient Unsupervised Shortcut Learning Detection and Mitigation in Transformers

Lukas Kuhn, Sari Sadiya, Jörg Schlötterer, Florian Buettner, Christin Seifert, Gemma Roig

ICCV 2025poster

Shortcut learning, i.e., a model's reliance on undesired features not directly relevant to the task, is a major challenge that severely limits the applications of machine learning algorithms, particularly when deploying them to assist in making sensitive decisions, such as in medical diagnostics. In…

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