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Over the last few years, Contextualized Pre-trained Neural Language Models, such as BERT, GPT, have shown significant gains in various NLP tasks.
On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel R Bowman, and Rachel Rudinger. 2019b · 1903
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Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 1907
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Learning the difference that makes a difference with counterfactually-augmented data
Divyansh Kaushik, Eduard Hovy, and Zachary C Lipton. 2019 · 1909
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Predictive biases in natural language processing models: A conceptual framework and overview
Deven Shah, H Andrew Schwartz, and Dirk Hovy. 2019 · 1912
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Don’t touch my projectile: Gender bias and stereotyping in syntactic examples
Monica Macaulay and Colleen Brice. 1997 · 1997
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Adversarial training for large neural language models
Xiaodong Liu, Hao Cheng, Pengcheng He, Weizhu Chen, Yu Wang, Hoifung Poon, and Jianfeng Gao. 2020 · 2004
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Reducing gender bias in neural machine translation as a domain adaptation problem
Danielle Saunders and Bill Byrne. 2020 · 2004
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Double-hard debias: Tailoring word embeddings for gender bias mitigation
Tianlu Wang, Xi Victoria Lin, Nazneen Fatema Rajani, Bryan McCann, Vicente Ordonez, and Caiming Xiong. 2020 · 2005
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Gender bias in multilingual embeddings and cross-lingual transfer
Jieyu Zhao, Subhabrata Mukherjee, Saghar Hosseini, Kai-Wei Chang, and Ahmed Hassan Awadallah. 2020 · 2005
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The social, psychological, and political causes of racial disparities in the american criminal justice system
Michael Tonry. 2010 · 2010
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai. 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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End-to-end neural coreference resolution
Kenton Lee, Luheng He, M. Lewis, and Luke Zettlemoyer. 2017 · 2017
Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru. 2018 · 2018
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Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
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Identifying and reducing gender bias in word-level language models
Shikha Bordia and Samuel R. Bowman. 2019 · 2019
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Proposed taxonomy for gender bias in text; a filtering methodology for the gender generalization subtype
Yasmeen Hitti, Eunbee Jang, Ines Moreno, and Carolyne Pelletier. 2019 · 2019
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Algorithmic bias? an empirical study of apparent gender-based discrimination in the display of stem career ads
Anja Lambrecht and Catherine Tucker. 2019 · 2019
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017 · 2017
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Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk. 2018 · 2018
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Masked language modeling
The Allen Institute for Artificial Intelligence
Cited in the paper.
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019a · 2019
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An empirical study on robustness to spurious correlations using pre-trained language models
Lifu Tu, Garima Lalwani, Spandana Gella, and He He. 2020 · 2020
Later among the works it cites.