L3Cube-IndicQuest: A Benchmark Question Answering Dataset for Evaluating Knowledge of LLMs in Indic Context

Pritika Rohera, Chaitrali Ginimav, Akanksha Salunke, Gayatri Sawant, Raviraj Joshi


Anthology ID:
2024.paclic-1.93
Volume:
Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
Month:
December
Year:
2024
Address:
Tokyo, Japan
Editors:
Nathaniel Oco, Shirley N. Dita, Ariane Macalinga Borlongan, Jong-Bok Kim
Venue:
PACLIC
SIG:
Publisher:
Tokyo University of Foreign Studies
Note:
Pages:
982–988
Language:
URL:
https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.93/
DOI:
Bibkey:
Cite (ACL):
Pritika Rohera, Chaitrali Ginimav, Akanksha Salunke, Gayatri Sawant, and Raviraj Joshi. 2024. L3Cube-IndicQuest: A Benchmark Question Answering Dataset for Evaluating Knowledge of LLMs in Indic Context. In Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation, pages 982–988, Tokyo, Japan. Tokyo University of Foreign Studies.
Cite (Informal):
L3Cube-IndicQuest: A Benchmark Question Answering Dataset for Evaluating Knowledge of LLMs in Indic Context (Rohera et al., PACLIC 2024)
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PDF:
https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.93.pdf