May 13, 2024, 4:46 a.m. | Rishav Hada, Safiya Husain, Varun Gumma, Harshita Diddee, Aditya Yadavalli, Agrima Seth, Nidhi Kulkarni, Ujwal Gadiraju, Aditya Vashistha, Vivek Sesha

cs.CL updates on arXiv.org arxiv.org

arXiv:2405.06346v1 Announce Type: new
Abstract: Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South. This paper presents the first comprehensive study delving into the nuanced landscape of gender bias in Hindi, the third most spoken language globally. Our study employs diverse mining techniques, computational models, field studies and sheds light on the limitations of current methodologies. Given the challenges faced with mining gender biased statements …

abstract arxiv bias challenges cs.cl english exploratory gender gender bias global hindi landscape language languages measuring paper research study technology type

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