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Word embeddings derived from human-generated corpora inherit strong gender bias which can be further amplified by downstream models.
Evaluating the underlying gender bias in contextualized word embeddings
Christine Basta, Marta Ruiz Costa-jussà, and Noe Casas. 2019 · 1904
Earlier work this paper cites.
Gender-preserving debiasing for pre-trained word embeddings
Masahiro Kaneko and Danushka Bollegala. 2019 · 1906
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Measuring bias in contextualized word representations
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W. Black, and Yulia Tsvetkov. 2019 · 1906
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Evaluating gender bias in machine translation
Gabriel Stanovsky, Noah A Smith, and Luke Zettlemoyer. 2019 · 1906
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Understanding undesirable word embedding associations
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019 · 1908
Earlier work this paper cites.
Category norms of verbal items in 56 categories a replication and extension of the connecticut category norms
William F. Battig and William E. Montague. 1969 · 1969
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Attributes in lexical acquisition
Abdulrahman Almuhareb. 2006 · 2006
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Bridging the gap between semantic theory and computational simulations: Proceedings of the esslli workshop on distributional lexical semantics
Marco Baroni, Stefan Evert, and Alessandro Lenci. 2008 · 2008
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
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Introduction to Information Retrieval
Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. 2008 · 2008
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How we blessed distributional semantic evaluation
Marco Baroni and Alessandro Lenci. 2011 · 2011
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Linguistic regularities in continuous space word representations
Tomas Mikolov, Wen-tau Yih, and Geoffrey Zweig. 2013c · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
End-to-end neural coreference resolution
Kenton Lee, Luheng He, Mike Lewis, and Luke Zettlemoyer. 2017 · 2017
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Frage: Frequency-agnostic word representation
Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tie-Yan Liu. 2018 · 2018
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All-but-the-top: Simple and effective postprocessing for word representations
Jiaqi Mu and Pramod Viswanath. 2018 · 2018
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Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
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Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them
Hila Gonen and Yoav Goldberg. 2019 · 2019
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Gender bias in contextualized word embeddings
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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 Tauman 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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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013a
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013b
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018a
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Learning gender-neutral word embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, and Kai-Wei Chang. 2018b
Cited in the paper.
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, and Kai-Wei Chang. 2019 · 2019
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Causal mediation analysis for interpreting neural nlp: The case of gender bias
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 2020 · 2020
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