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        <title>GD-COMET: A Geo-Diverse Commonsense Inference Model</title>
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    <abstract>With the increasing integration of AI into everyday life, it‘s becoming crucial to design AI systems to 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.</abstract>
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    <identifier type="doi">10.18653/v1/2023.emnlp-main.496</identifier>
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%0 Conference Proceedings
%T GD-COMET: A Geo-Diverse Commonsense Inference Model
%A Bhatia, Mehar
%A Shwartz, Vered
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F bhatia-shwartz-2023-gd
%X With the increasing integration of AI into everyday life, it‘s becoming crucial to design AI systems to 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.
%R 10.18653/v1/2023.emnlp-main.496
%U https://aclanthology.org/2023.emnlp-main.496/
%U https://doi.org/10.18653/v1/2023.emnlp-main.496
%P 7993-8001

Markdown (Informal)

[GD-COMET: A Geo-Diverse Commonsense Inference Model](https://aclanthology.org/2023.emnlp-main.496/) (Bhatia & Shwartz, EMNLP 2023)

• GD-COMET: A Geo-Diverse Commonsense Inference Model (Bhatia & Shwartz, EMNLP 2023)

ACL

• Mehar Bhatia and Vered Shwartz. 2023. GD-COMET: A Geo-Diverse Commonsense Inference Model. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 7993–8001, Singapore. Association for Computational Linguistics.