3 papers
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.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.CL2026
Modular Expert Merging for Biomedical Retrieval
Sameh Khattab, Jean-Philippe Corbeil, Osman Alperen Çinar-Koraş +5
Adapting general-purpose LLMs into domain-specialized dense retrievers typically requires large-scale training on mixed-domain data. We show that merging independently trained doma…