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We present WinoQueer: a benchmark specifically designed to measure whether large language models (LLMs) encode biases that are harmful to the LGBTQ+ community.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
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An analysis of gender bias studies in natural language processing
Marta R. Costa-jussà. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Decolonising speech and language technology
Steven Bird. 2020 · 2020
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Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
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Detecting gender stereotypes: Lexicon vs. supervised learning methods
Jenna Cryan, Shiliang Tang, Xinyi Zhang, Miriam Metzger, Haitao Zheng, and Ben Y. Zhao. 2020 · 2020
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ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
BERTweet: A pre-trained language model for English tweets
Dat Quoc Nguyen, Thanh Vu, and Anh Tuan Nguyen. 2020 · 2020
Cited alongside, same era.
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
Cited alongside, same era.
Quantifying social biases in NLP: A generalization and empirical comparison of extrinsic fairness metrics
Paula Czarnowska, Yogarshi Vyas, and Kashif Shah. 2021 · 2021
Cited alongside, same era.
Towards winoqueer: Developing a benchmark for anti-queer bias in large language models
Virginia K. Felkner, Ho-Chun Herbert Chang, Eugene Jang, and Jonathan May. 2022 · 2022
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French CrowS-pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English
Aurélie Névéol, Yoann Dupont, Julien Bezançon, and Karën Fort. 2022 · 2022
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“I’m sorry to hear that”: Finding new biases in language models with a holistic descriptor dataset
Eric Michael Smith, Melissa Hall, Melanie Kambadur, Eleonora Presani, and Adina Williams. 2022 · 2022
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BLOOM: A 176b-parameter open-access multilingual language model
BigScience Workshop. 2022 · 2022
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021
Cited alongside, same era.
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities
Nenad Tomasev, Kevin R. McKee, Jackie Kay, and Shakir Mohamed. 2021 · 2021
Cited alongside, same era.
Theory-grounded measurement of U.S. social stereotypes in English language models
Yang Cao, Anna Sotnikova, Hal Daumé III, Rachel Rudinger, and Linda Zou. 2022 · 2022
Cited alongside, same era.
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer. 2022 · 2022
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explosion/spaCy: v3.5.0: New CLI commands, language updates, bug fixes and much more
Ines Montani, Matthew Honnibal, Matthew Honnibal, Sofie Van Landeghem, Adriane Boyd, Henning Peters, Paul O’Leary McCann, jim geovedi, Jim O’Regan, Maxim Samsonov, György Orosz, Daniël de Kok, Duygu Altinok, Søren Lind Kristiansen, Madeesh Kannan, Raphaël Bournhonesque, Lj Miranda, Peter Baumgartner, Edward, Explosion Bot, Richard Hudson, Raphael Mitsch, Roman, Leander Fiedler, Ryn Daniels, Wannaphong Phatthiyaphaibun, Grégory Howard, Yohei Tamura, and Sam Bozek. 2023 · 2023
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Theories of “gender” in nlp bias research
Hannah Devinney, Jenny Björklund, and Henrik Björklund. 2022 · 2083
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