@inproceedings{hosain-morol-2025-intrinsic,
title = "Intrinsic Linguistic Bias in Formal vs. Informal {B}engali Pragmatics with Progressive Context Inflation",
author = "Hosain, Md Tanzib and
Morol, Md Kishor",
editor = "Inui, Kentaro and
Sakti, Sakriani and
Wang, Haofen and
Wong, Derek F. and
Bhattacharyya, Pushpak and
Banerjee, Biplab and
Ekbal, Asif and
Chakraborty, Tanmoy and
Singh, Dhirendra Pratap",
booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
month = dec,
year = "2025",
address = "Mumbai, India",
publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-ijcnlp.21/",
pages = "384--396",
ISBN = "979-8-89176-303-6",
abstract = "The social biases inherent in language models necessitate a critical analysis of their social influence in many linguistic situations because of their extensive use. This study investigates gender bias in Bengali language models by highlighting the unique linguistic challenges posed by its complex morphology, dialectical variations, and distinctions between formal and informal language versions. While prior research on social bias in Bengali has provided foundational insights, it has not adequately addressed the nuances arising from these variations. This research extends to measuring intrinsic gender bias in both formal and informal Bengali, analyzing the impact of context lengths on bias detection, and proposing modifications to existing techniques to enhance their applicability to Bengali. Addressing these, the study aims to contribute to developing more inclusive and representative bias measurement methodologies for underrepresented languages. We open the source code and data at https://github.com/kraritt/b-bias-ctext."
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%0 Conference Proceedings
%T Intrinsic Linguistic Bias in Formal vs. Informal Bengali Pragmatics with Progressive Context Inflation
%A Hosain, Md Tanzib
%A Morol, Md Kishor
%Y Inui, Kentaro
%Y Sakti, Sakriani
%Y Wang, Haofen
%Y Wong, Derek F.
%Y Bhattacharyya, Pushpak
%Y Banerjee, Biplab
%Y Ekbal, Asif
%Y Chakraborty, Tanmoy
%Y Singh, Dhirendra Pratap
%S Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
%D 2025
%8 December
%I The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
%C Mumbai, India
%@ 979-8-89176-303-6
%F hosain-morol-2025-intrinsic
%X The social biases inherent in language models necessitate a critical analysis of their social influence in many linguistic situations because of their extensive use. This study investigates gender bias in Bengali language models by highlighting the unique linguistic challenges posed by its complex morphology, dialectical variations, and distinctions between formal and informal language versions. While prior research on social bias in Bengali has provided foundational insights, it has not adequately addressed the nuances arising from these variations. This research extends to measuring intrinsic gender bias in both formal and informal Bengali, analyzing the impact of context lengths on bias detection, and proposing modifications to existing techniques to enhance their applicability to Bengali. Addressing these, the study aims to contribute to developing more inclusive and representative bias measurement methodologies for underrepresented languages. We open the source code and data at https://github.com/kraritt/b-bias-ctext.
%U https://aclanthology.org/2025.findings-ijcnlp.21/
%P 384-396
Markdown (Informal)
[Intrinsic Linguistic Bias in Formal vs. Informal Bengali Pragmatics with Progressive Context Inflation](https://aclanthology.org/2025.findings-ijcnlp.21/) (Hosain & Morol, Findings 2025)
ACL