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Natural Language Processing (NLP) systems learn harmful societal biases that cause them to amplify inequality as they are deployed in more and more situations.
LOGAN: Local group bias detection by clustering
Jieyu Zhao and Kai-Wei Chang. 2020 · 1977
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Measuring individual differences in implicit cognition: the implicit association test
A. Greenwald, D. McGhee, and J. L. Schwartz. 1998 · 1998
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013 · 2013
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PRESTIGIO Y ESTIGMATIZACIÓN DE 60 NOMBRES PROPIOS EN 40 SUJETOS DE NIVEL EDUCACIONAL SUPERIOR
Gastã Salamanca and Lidia Pereira. 2013 · 2013
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Simlex-999: Evaluating semantic models with (genuine) similarity estimation
Felix Hill, Roi Reichart, and A. Korhonen. 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 Y. Zou, Venkatesh Saligrama, and Adam Tauman Kalai. 2016 · 2016
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Problems with evaluation of word embeddings using word similarity tasks
Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi, and Chris Dyer. 2016 · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro. 2016 · 2016
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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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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The trouble with bias. (keynote at neurips)
Kate Crawford. 2017 · 2017
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End-to-end neural coreference resolution
Kenton Lee, Luheng He, M. Lewis, and Luke Zettlemoyer. 2017 · 2017
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Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddings
K. McCurdy and Oguz Serbetci. 2017 · 2017
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Semantic specialization of distributional word vector spaces using monolingual and cross-lingual constraints
Nikola Mrksic, Ivan Vulic, Diarmuid Ó Séaghdha, Ira Leviant, Roi Reichart, Milica Gasic, Anna Korhonen, and Steve J. Young. 2017 · 2017
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Gender and dialect bias in youtube’s automatic captions
Rachael Tatman. 2017 · 2017
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Ontonotes : A large training corpus for enhanced processing
R. Weischedel, E. Hovy, M. Marcus, and Martha Palmer. 2017 · 2017
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Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Scott Sorensen, Nithum Thain, and Lucy Vasserman. 2018 · 2018
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Large scale crowdsourcing and characterization of twitter abusive behavior
Antigoni Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos, and Nicolas Kourtellis. 2018 · 2018
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Are we consistently biased? multidimensional analysis of biases in distributional word vectors
Anne Lauscher and Goran Glavas. 2019 · 2019
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On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019 · 2019
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The risk of racial bias in hate speech detection
Maarten Sap, D. Card, Saadia Gabriel, Yejin Choi, and Noah A. Smith. 2019 · 2019
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The role of protected class word lists in bias identification of contextualized word representations
João Sedoc and Lyle Ungar. 2019 · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
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Evaluating gender bias in machine translation
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Semeval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter
Valerio Basile, C. Bosco, E. Fersini, Debora Nozza, V. Patti, F. Pardo, P. Rosso, and M. Sanguinetti. 2019 · 2019
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Racial bias in hate speech and abusive language detection datasets
Thomas Davidson, Debasmita Bhattacharya, and Ingmar Weber. 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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Understanding undesirable word embedding associations
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019 · 2019
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How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
Goran Glavas, Robert Litschko, Sebastian Ruder, and Ivan Vulic. 2019 · 2019
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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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How does grammatical gender affect noun representations in gender-marking languages?
Hila Gonen, Yova Kementchedjhieva, and Yoav Goldberg. 2019 · 2019
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Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019 · 2019
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Gender bias in contextualized word embeddings
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, and Kai-Wei Chang. 2019 · 2019
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Examining gender bias in languages with grammatical gender
Pei Zhou, Weijia Shi, Jieyu Zhao, Kuan-Hao Huang, Muhao Chen, Ryan Cotterell, and Kai-Wei Chang. 2019 · 2019
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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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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
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A general framework for implicit and explicit debiasing of distributional word vector spaces
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Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 2020 · 2020
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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 · 2020
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