Speaker
Hassan Hussein
(LUH)
Description
Scholarly knowledge curation faces challenges due to diverse methodologies across scientific fields. Leveraging Large Language Models (LLMs) like GPT-3.5 and visual models, we enhance AI explainability and trustworthiness in knowledge curation. Our approach integrates LLMs and VLMS with the Open Research Knowledge Graph (ORKG) and employs prompt engineering for accurate data extraction from academic literature. This collaborative framework merges neural capabilities with symbolic knowledge graphs and human expertise, addressing practical challenges and promoting transparent, reliable AI applications in scientific research.
Primary author
Hassan Hussein
(LUH)
