GD-COMET: A Geo-Diverse Commonsense Inference Model

Mehar Bhatia, Vered Shwartz

Submission Type: Regular Short Paper

Submission Track: Commonsense Reasoning

Submission Track 2: Computational Social Science and Cultural Analytics

Keywords: commonsense reasoning, culture-aware NLP, geo-diverse applications

TL;DR: In this paper, we introduce GD-COMET, a geo-diverse commonsense inference model that generates culturally nuanced knowledge, enabling more inclusive and culturally aware AI systems.

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.

Submission Number: 4269