Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models

Author:

Khandelwal Khyati1ORCID,Tonneau Manuel1ORCID,Bean Andrew M.1ORCID,Kirk Hannah Rose1ORCID,Hale Scott A.1ORCID

Affiliation:

1. University of Oxford, United Kingdom

Publisher

ACM

Reference71 articles.

1. Senthil Kumar B, Pranav Tiwari, Aman Chandra Kumar, and Aravindan Chandrabose. 2022. Casteism in India, but Not Racism - a Study of Bias in Word Embeddings of Indian Languages. In Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference, Kolawole Adebayo, Rohan Nanda, Kanishk Verma, and Brian Davis (Eds.). European Language Resources Association, Marseille, France, 1–7. https://aclanthology.org/2022.lateraisse-1.1

2. ‘Race’, Religion and Riots: The ‘Racialization’ of Communal Identity and Conflict in India

3. The Pre-history of ‘;Communalism’? Religious Conflict in India, 1700–1860

4. Hugo Berg, Siobhan Mackenzie Hall, Yash Bhalgat, Wonsuk Yang, Hannah Rose Kirk, Aleksandar Shtedritski, and Max Bain. 2022. A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning. arXiv preprint arXiv:2203.11933 (2022).

5. Shaily Bhatt, Sunipa Dev, Partha Talukdar, Shachi Dave, and Vinodkumar Prabhakaran. 2022. Re-contextualizing fairness in NLP: The case of India. arXiv preprint arXiv:2209.12226 (2022).

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