Publications (6)
SteuerLLM: Local specialized large language model for German tax law analysis
Sebastian Wind, Jeta Sopa, Laurin Schmid +8
Large language models (LLMs) demonstrate strong general reasoning and language understanding, yet their performance degrades in domains governed by strict formal rules, precise ter…
AI Application Benchmarking: Power-Aware Performance Analysis for Vision and Language Models
Martin Mayr, Sebastian Wind, Lukas Schröder +4
Artificial Intelligence (AI) workloads drive a rapid expansion of high-performance computing (HPC) infrastructures and increase their power and energy demands towards a critical le…
Multi-step retrieval and reasoning improves radiology question answering with large language models
Sebastian Wind, Jeta Sopa, Daniel Truhn +9
Clinical decision-making in radiology increasingly benefits from artificial intelligence (AI), particularly through large language models (LLMs). However, traditional retrieval-aug…
AMD-HookNet++: Evolution of AMD-HookNet with Hybrid CNN-Transformer Feature Enhancement for Glacier Calving Front Segmentation
Fei Wu, Marcel Dreier, Nora Gourmelon +6
The dynamics of glaciers and ice shelf fronts significantly impact the mass balance of ice sheets and coastal sea levels. To effectively monitor glacier conditions, it is crucial t…
Safety and accuracy follow different scaling laws in clinical large language models
Sebastian Wind, Tri-Thien Nguyen, Jeta Sopa +9
Clinical LLMs are often scaled by increasing model size, context length, retrieval complexity, or inference-time compute, with the implicit expectation that higher accuracy implies…
Agentic retrieval-augmented reasoning reshapes collective reliability under model variability in radiology question answering
Mina Farajiamiri, Jeta Sopa, Saba Afza +9
Agentic retrieval-augmented reasoning pipelines are increasingly used to structure how large language models (LLMs) incorporate external evidence in clinical decision support. Thes…