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Reporting and providing test sets for harmful bias in NLP applications is essential for building a robust understanding of the current problem.
Contextual correlates of synonymy
Herbert Rubenstein and John B. Goodenough. 1965 · 1965
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Learning gender-neutral word embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, and Kai-Wei Chang. 2018b · 1968
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V-measure: A conditional entropy-based external cluster evaluation measure
Andrew Rosenberg and Julia Hirschberg. 2007 · 2007
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Measuring word relatedness using heterogeneous vector space models
Wen-tau Yih and Vahed Qazvinian. 2012 · 2012
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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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Multimodal distributional semantics
E. Bruni N. K. Tran M. Baroni. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 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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Simlex-999: Evaluating semantic models with (genuine) similarity estimation
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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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A decomposable attention model for natural language inference
Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 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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How to evaluate word embeddings? on importance of data efficiency and simple supervised tasks
Stanislaw Jastrzebski, Damian Lesniak, and Wojciech Marian Czarnecki. 2017 · 2017
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Gender-preserving debiasing for pre-trained word embeddings
Masahiro Kaneko and Danushka Bollegala. 2019 · 2019
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Mitigating gender bias in natural language processing: Literature review
Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, and William Yang Wang. 2019 · 2019
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Decision-directed data decomposition
Brent D. Davis, Ethan Jackson, and Daniel J. Lizotte. 2020 · 2020
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Nurse is closer to woman than surgeon? mitigating gender-biased proximities in word embeddings
Vaibhav Kumar, Tenzin Singhay Bhotia, Vaibhav Kumar, and Tanmoy Chakraborty. 2020 · 2020
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A general framework for implicit and explicit debiasing of distributional word vector spaces
Anne Lauscher, Goran Glavaš, Simone Paolo Ponzetto, and Ivan Vulić. 2019 · 2020
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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 · 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
Cited alongside, same era.
On measuring and mitigating biased inferences of word embeddings
Sunipa Dev, Tao Li, Jeff M. Phillips, and Vivek Srikumar. 2020a
Cited in the paper.
Oscar: Orthogonal subspace correction and rectification of biases in word embeddings
Sunipa Dev, Tao Li, Jeff M Phillips, and Vivek Srikumar. 2020b
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg 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
Cited in the paper.
Null it out: Guarding protected attributes by iterative nullspace projection
Shauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton, and Yoav Goldberg. 2020 · 2020
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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 · 2020
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