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Discriminatory gender biases have been found in Pre-trained Language Models (PLMs) for multiple languages.
Intrinsic bias metrics do not correlate with application bias
Seraphina Goldfarb-Tarrant, Rebecca Marchant, Ricardo Muñoz Sánchez, Mugdha Pandya, and Adam Lopez. 2021 · 1940
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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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Microsoft COCO: common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll’a r, and C. Lawrence Zitnick. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, and Adam Kalai. 2016 · 2016
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Adding chinese captions to images
Xirong Li, Weiyu Lan, Jianfeng Dong, and Hailong Liu. 2016 · 2016
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Cross-lingual image caption generation
Takashi Miyazaki and Nobuyuki Shimizu. 2016 · 2016
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Juman++: A morphological analysis toolkit for scriptio continua
Arseny Tolmachev, Daisuke Kawahara, and Sadao Kurohashi. 2018 · 2018
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Bias in bios: A case study of semantic representation bias in a high-stakes setting
Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, and Adam Tauman Kalai. 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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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 · 2019
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On measuring and mitigating biased inferences of word embeddings
Sunipa Dev, Tao Li, Jeff M. Phillips, and Vivek Srikumar. 2020 · 2020
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OCNLI: Original Chinese Natural Language Inference
Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kübler, and Lawrence Moss. 2020 · 2020
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021
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Evaluating gender bias in natural language inference
Shanya Sharma, Manan Dey, and Koustuv Sinha. 2021 · 2021
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On the intrinsic and extrinsic fairness evaluation metrics for contextualized language representations
Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, and Aram Galstyan. 2022 · 2022
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On measures of biases and harms in NLP
Sunipa Dev, Emily Sheng, Jieyu Zhao, Aubrie Amstutz, Jiao Sun, Yu Hou, Mattie Sanseverino, Jiin Kim, Akihiro Nishi, Nanyun Peng, and Kai-Wei Chang. 2022 · 2022
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Unmasking the mask – evaluating social biases in masked language models
Masahiro Kaneko and Danushka Bollegala. 2022 · 2022
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Can existing methods debias languages other than English? first attempt to analyze and mitigate Japanese word embeddings
Masashi Takeshita, Yuki Katsumata, Rafal Rzepka, and Kenji Araki. 2020 · 2020
Cited alongside, same era.
Measuring and reducing gendered correlations in pre-trained models
Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Ed H. Chi, and Slav Petrov. 2020 · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Cited alongside, same era.
Multilingualization of natural language inference datasets using machine translation
Takumi Yoshikoshi, Daisuke Kawahara, and Sadao Kurohashi. 2020 · 2020
Cited alongside, same era.
Gender bias hidden behind Chinese word embeddings: The case of Chinese adjectives
Meichun Jiao and Ziyang Luo. 2021 · 2021
Cited alongside, same era.
Debiasing isn’t enough! – on the effectiveness of debiasing MLMs and their social biases in downstream tasks
Masahiro Kaneko, Danushka Bollegala, and Naoaki Okazaki. 2022a
Cited in the paper.
Comparing intrinsic gender bias evaluation measures without using human annotated examples
Masahiro Kaneko, Danushka Bollegala, and Naoaki Okazaki. 2023a
Cited in the paper.
Gender bias in masked language models for multiple languages
Masahiro Kaneko, Aizhan Imankulova, Danushka Bollegala, and Naoaki Okazaki. 2022b · 2022
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JGLUE: Japanese general language understanding evaluation
Kentaro Kurihara, Daisuke Kawahara, and Tomohide Shibata. 2022 · 2022
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Socially aware bias measurements for Hindi language representations
Vijit Malik, Sunipa Dev, Akihiro Nishi, Nanyun Peng, and Kai-Wei Chang. 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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In-contextual bias suppression for large language models
Daisuke Oba, Masahiro Kaneko, and Danushka Bollegala. 2023 · 2023
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