[29] Vijit Malik, Sunipa Dev, Akihiro Nishi, Nanyun Peng, and Kai-Wei Chang. Socially aware bias measurements for Hindi language representations. In Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), short, 2022.
[30] Neha Mishra. India and colorism: The finer nuances. 14 WASH. U. GLOBAL STUD. L. REV. 725, 2015.
[31] Moin Nadeem, Anna Bethke, and Siva Reddy. Stereoset: Measuring stereotypical bias in pretrained language models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 5356-5371, 2021.
[32] Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel Bowman. Crows-pairs: A challenge dataset for measuring social biases in masked language models. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1953-1967, 2020.
[33] Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee, and Kai-Wei Chang. Factoring the matrix of domination: A critical review and reimagination of intersectionality in ai fairness, 2023.
[34] Nataraj P. Mental pictures of college girls of hindus, muslims and christians, 1965.
[35] Vinodkumar Prabhakaran, Rida Qadri, and Ben Hutchinson. Cultural incongruencies in artificial intelligence, 2022.
[36] Rida Qadri, Renee Shelby, Cynthia L. Bennett, and Emily Denton. Ai's regimes of representation: A community-centered study of text-to-image models in south asia. In ACM FAccT (to appear), May 2023.
[37] Iyad Rahwan. Society-in-the-loop: programming the algorithmic social contract. Ethics and Information Technology, 20(1):5-14, aug 2017.
[38] Shauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton, and Yoav Goldberg. Null it out: Guarding protected attributes by iterative nullspace projection. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7237-7256, Online, July 2020. Association for Computational Linguistics.
[39] Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. High-resolution image synthesis with latent diffusion models. CoRR, abs/2112.10752, 2021.
[40] Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, and Vinodkumar Prabhakaran. Reimagining algorithmic fairness in india and beyond. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, FAccT '21, page 315-328, New York, NY, USA, 2021. Association for Computing Machinery.
[41] Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. Participation is not a design fix for machine learning, 2020.
[42] Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le. Lamda: Language models for dialog applications, 2022.
[43] Adina Williams, Nikita Nangia, and Samuel Bowman. A broad-coverage challenge corpus for sentence understanding through inference. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 1112–1122. Association for Computational Linguistics, 2018.
[44] Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. Xlnet: Generalized autoregressive pretraining for language understanding. Advances in neural information processing systems, 32, 2019.
[45] Ann Yuan, Andy Coenen, Emily Reif, and Daphne Ippolito. Wordcraft: Story writing with large language models. In 27th International Conference on Intelligent User Interfaces, IUI '22, page 841-852, New York, NY, USA, 2022. Association for Computing Machinery.