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Scholarly Question Answering Using Large Language Models in the NFDI4DataScience Gateway

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet

Authors

This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4DS Gateway, as a foundational framework, offers a unified and intuitive interface for querying various scientific databases using federated search. The RAG-based scholarly QA, powered by a Large Language Model (LLM), facilitates dynamic interaction with search results, enhancing filtering capabilities and fostering a conversational engagement with the Gateway search. The effectiveness of both the Gateway and the scholarly QA system is demonstrated through experimental analysis.

OriginalspracheEnglisch
TitelNatural Scientific Language Processing and Research Knowledge Graphs - 1st International Workshop, NSLP 2024, Proceedings
HerausgeberGeorg Rehm, Stefan Dietze, Sonja Schimmler, Frank Krüger
Anzahl der Seiten16
VerlagSpringer Science and Business Media Deutschland
Erscheinungsdatum2024
Seiten3-18
ISBN (Print)978-3-031-65793-1
ISBN (elektronisch)978-3-031-65794-8
DOIs
PublikationsstatusErschienen - 2024
Veranstaltung1st International Workshop on Natural Scientific Language Processing and Research Knowledge Graphs - NSLP 2024 - Hersonissos, Hersonissos, Griechenland
Dauer: 27.05.2024 → 27.05.2024
Konferenznummer: 1
https://nfdi4ds.github.io/nslp2024/

Bibliographische Notiz

Publisher Copyright:
© The Author(s) 2024.

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Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung

DOI

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