NFDIxCS Soiree #10: How LLM's Can Make Scientific Literature More Accessible
How can Large Language Models help researchers understand papers faster, extract key concepts, and publish more FAIRly? In this NFDIxCS Soirée, we show how LLM-based information extraction can practically support researchers in their workflows.
DOI: https://meetgi.zoom.us/j/62668240365
Description
The ever-growing flood of publications makes it difficult to keep track of research and to ensure that research outputs remain findable and reusable in line with FAIR principles. Within the NFDIxCS project, a system has been developed that uses Large Language Models to semantically extract key concepts from scientific articles – such as research questions, methods, or main findings.
In this Soirée, two short impulse talks (around 8 minutes each) will provide insights into:
how LLMs can be used to automatically scan scientific texts for key information,
how this information can be structured and, for example, linked to knowledge graphs,
what initial evaluation results and usage scenarios emerge from pilot studies with researchers.
The talks will be followed by time for questions and discussion.
Speakers:
Samy Ateia (NFDIxCS)
Moayad Almohaishi (NFDIxCS)