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EMNLP 2023mainmain

GD-COMET: A Geo-Diverse Commonsense Inference Model

Mehar Bhatia, Vered Shwartz

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2023.emnlp-main.496 ↗

摘要

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.