most citedLLM-Based Information Extraction to Support Scientific Literature Research and Publication Workflows

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2025

MedNuggetizer: Confidence-Based Information Nugget Extraction from Medical Documents

Gregor Donabauer, Samy Ateia, Udo Kruschwitz +6

We present MedNuggetizer, https://mednugget-ai.de/; access is available upon request.}, a tool for query-driven extraction and clustering of information nuggets from medical docume…

cs.DL20252 cited

LLM-Based Information Extraction to Support Scientific Literature Research and Publication Workflows

Samy Ateia, Udo Kruschwitz, Melanie Scholz +2

The increasing volume of scholarly publications requires advanced tools for efficient knowledge discovery and management. This paper introduces ongoing work on a system using Large…

cs.CL2025

Can Language Models Critique Themselves? Investigating Self-Feedback for Retrieval Augmented Generation at BioASQ 2025

Samy Ateia, Udo Kruschwitz

Agentic Retrieval Augmented Generation (RAG) and 'deep research' systems aim to enable autonomous search processes where Large Language Models (LLMs) iteratively refine outputs. Ho…

cs.IR2025

Query Smarter, Trust Better? Exploring Search Behaviours for Verifying News Accuracy

David Elsweiler, Samy Ateia, Markus Bink +8

While it is often assumed that searching for information to evaluate misinformation will help identify false claims, recent work suggests that search behaviours can instead reinfor…

cs.CL20241 cited

BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A

Samy Ateia, Udo Kruschwitz

We present BioRAGent, an interactive web-based retrieval-augmented generation (RAG) system for biomedical question answering. The system uses large language models (LLMs) for query…