An Empirical Study on the Characteristics of Bias upon Context Length Variation for Bangla

Jayanta Sadhu, Ayan Khan, Abhik Bhattacharjee, Rifat Shahriyar

Abstract
Pretrained language models inherently exhibit various social biases, prompting a crucial examination of their social impact across various linguistic contexts due to their widespread usage. Previous studies have provided numerous methods for intrinsic bias measurements, predominantly focused on high-resource languages. In this work, we aim to extend these investigations to Bangla, a low-resource language. Specifically, in this study, we (1) create a dataset for intrinsic gender bias measurement in Bangla, (2) discuss necessary adaptations to apply existing bias measurement methods for Bangla, and (3) examine the impact of context length variation on bias measurement, a factor that has been overlooked in previous studies. Through our experiments, we demonstrate a clear dependency of bias metrics on context length, highlighting the need for nuanced considerations in Bangla bias analysis. We consider our work as a stepping stone for bias measurement in the Bangla Language and make all of our resources publicly available to support future research.
Anthology ID:
2024.findings-acl.88
Volume:
Findings of the Association for Computational Linguistics: ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1501–1520
Language:
URL:
https://aclanthology.org/2024.findings-acl.88
DOI:
10.18653/v1/2024.findings-acl.88
Bibkey:
Cite (ACL):
Jayanta Sadhu, Ayan Khan, Abhik Bhattacharjee, and Rifat Shahriyar. 2024. An Empirical Study on the Characteristics of Bias upon Context Length Variation for Bangla. In Findings of the Association for Computational Linguistics: ACL 2024, pages 1501–1520, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
An Empirical Study on the Characteristics of Bias upon Context Length Variation for Bangla (Sadhu et al., Findings 2024)
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