GD-COMET: A Geo-Diverse Commonsense Inference Model

Mehar Bhatia; Vered Shwartz

doi:10.18653/v1/2023.emnlp-main.496

GD-COMET: A Geo-Diverse Commonsense Inference Model

Mehar Bhatia, Vered Shwartz

University of British Columbia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

With the increasing integration of AI into everyday life, it's becoming crucial to design AI systems that serve users from diverse backgrounds by making them culturally aware. In this paper, we present GD-COMET, a geo-diverse version of the COMET commonsense inference model. GD-COMET goes beyond Western commonsense knowledge and is capable of generating inferences pertaining to a broad range of cultures. We demonstrate the effectiveness of GD-COMET through a comprehensive human evaluation across 5 diverse cultures, as well as extrinsic evaluation on a geo-diverse task. The evaluation shows that GD-COMET captures and generates culturally nuanced commonsense knowledge, demonstrating its potential to benefit NLP applications across the board and contribute to making NLP more inclusive.

Original language	English
Title of host publication	EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings
Editors	Houda Bouamor, Juan Pino, Kalika Bali
Publisher	Association for Computational Linguistics (ACL)
Pages	7993-8001
Number of pages	9
ISBN (Electronic)	9798891760608
DOIs	https://doi.org/10.18653/v1/2023.emnlp-main.496
State	Published - 2023
Externally published	Yes
Event	2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023 - Hybrid, Singapore, Singapore Duration: 6 Dec 2023 → 10 Dec 2023

Publication series

Name	EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference	2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023
Country/Territory	Singapore
City	Hybrid, Singapore
Period	6/12/23 → 10/12/23

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

Funding

This work was funded, in part, by the Vector Institute for AI, Canada CIFAR AI Chairs program, an NSERC discovery grant, and a research gift from AI2. Finally, we sincerely thank Sahithya Ravi, Aditya Chinchure, Ward Pennink and Jan Zimny for valuable feedback and discussions.

Funders	Funder number
Natural Sciences and Engineering Research Council of Canada
Vector Institute

Access to Document

10.18653/v1/2023.emnlp-main.496

Cite this

Bhatia, M., & Shwartz, V. (2023). GD-COMET: A Geo-Diverse Commonsense Inference Model. In H. Bouamor, J. Pino, & K. Bali (Eds.), EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 7993-8001). (EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.emnlp-main.496

Bhatia, Mehar ; Shwartz, Vered. / GD-COMET : A Geo-Diverse Commonsense Inference Model. EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings. editor / Houda Bouamor ; Juan Pino ; Kalika Bali. Association for Computational Linguistics (ACL), 2023. pp. 7993-8001 (EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings).

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Bhatia, M & Shwartz, V 2023, GD-COMET: A Geo-Diverse Commonsense Inference Model. in H Bouamor, J Pino & K Bali (eds), EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings. EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings, Association for Computational Linguistics (ACL), pp. 7993-8001, 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Hybrid, Singapore, Singapore, 6/12/23. https://doi.org/10.18653/v1/2023.emnlp-main.496

GD-COMET: A Geo-Diverse Commonsense Inference Model. / Bhatia, Mehar; Shwartz, Vered.
EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings. ed. / Houda Bouamor; Juan Pino; Kalika Bali. Association for Computational Linguistics (ACL), 2023. p. 7993-8001 (EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Bhatia M, Shwartz V. GD-COMET: A Geo-Diverse Commonsense Inference Model. In Bouamor H, Pino J, Bali K, editors, EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL). 2023. p. 7993-8001. (EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings). doi: 10.18653/v1/2023.emnlp-main.496

GD-COMET: A Geo-Diverse Commonsense Inference Model

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