papers

Publications (6)

cs.CL2025

Does Biomedical Training Lead to Better Medical Performance?

Amin Dada, Marie Bauer, Amanda Butler Contreras +4

Large Language Models (LLMs) are expected to significantly contribute to patient care, diagnostics, and administrative processes. Emerging biomedical LLMs aim to address healthcare…

cs.CV2025

Automatic Fine-grained Segmentation-assisted Report Generation

Frederic Jonske, Constantin Seibold, Osman Alperen Koras +6

Reliable end-to-end clinical report generation has been a longstanding goal of medical ML research. The end goal for this process is to alleviate radiologists' workloads and provid…

cs.AI2026

Configurable Clinical Information Extraction with Agentic RAG: What Works, What Breaks, and Why

Osman Alperen Çinar-Koraş, Marie Bauer, Sameh Khattab +7

Patient contexts span hundreds of heterogeneous documents and thousands of structured data points, yet the document-level metadata that AI systems need for retrieval and triage is…

cs.CL2024

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding

Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17

Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…

cs.IR2026

AIANO: Enhancing Information Retrieval with AI-Augmented Annotation

Sameh Khattab, Marie Bauer, Lukas Heine +3

The rise of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) has rapidly increased the need for high-quality, curated information retrieval datasets. These dat…

cs.CL2025

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters

Amin Dada, Osman Alperen Koras, Marie Bauer +4

While increasing patients' access to medical documents improves medical care, this benefit is limited by varying health literacy levels and complex medical terminology. Large langu…