MaScQA: investigating materials science knowledge of large language models-Reference-Cited by-同舟云学术

MaScQA: investigating materials science knowledge of large language models

Published:2024 Issue: Volume: Page:
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Zaki Mohd¹^ORCID,Jayadeva ²³^ORCID,Mausam ³⁴^ORCID,Krishnan N. M. Anoop¹³^ORCID

Affiliation:

1. Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

2. Department of Electrical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

3. Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

4. Department of Computer Science & Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

Abstract

Different materials science domains from which questions are present in Materials Science Question Answering (MaScQA) database.

Funder

Indian Institute of Technology Delhi

Vikram Sarabhai Space Centre

International Business Machines Corporation

Google

Board of Research in Nuclear Sciences

Microsoft

Wipro

Ministry of Education, India

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/DD/D3DD00188A

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