Fetching the paper…
Reading the bibliography…
Word vector representations are well developed tools for various NLP and Machine Learning tasks and are known to retain significant semantic and syntactic structure of languages.
WordNet: An Electronic Lexical Database
Christiane Fellbaum · 1998
Earlier work this paper cites.
Placing search in context : The concept revisited
L Finkelstein, E Gabrilovich, Y Matias, E Rivlin, Z Solan, G Wolfman, and etal · 2002
Earlier work this paper cites.
Nltk: The natural language toolkit
Edward Loper and Steven Bird · 2002
Earlier work this paper cites.
Evaluating the predictive validity of the compas risk and needs assessment system
Tim Brennan, William Dieterich, and Beate Ehret · 2009
Earlier work this paper cites.
Consumer credit-risk models via machine-learning algorithms
Amir E. Khandani, Adlar J. Kim, and Andrew Lo · 2010
Earlier work this paper cites.
Neural word embedding as implicit matrix factorization
Omer Levy and Yoav Goldberg · 2013
Earlier work this paper cites.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Cited alongside, same era.
Linguistic regularities of sparse and explicit word representations
Omer Levy and Yoav Goldberg · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning · 2014
Cited alongside, same era.
Simlex-999 : Evaluating semantic models with (genuine) similarity estimation
F Hill, R Reichart, and A Korhonen · 2015
Cited alongside, same era.
https://www.ssa.gov/oact/babynames/
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
T Bolukbasi, K W Chang, J Zou, V Saligrama, and A Kalai · 2016
Later among the works it cites.
Quantifying and reducing bias in word embeddings
T Bolukbasi, K W Chang, J Zou, V Saligrama, and A Kalai · 2016
Later among the works it cites.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan · 2017
Later among the works it cites.
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
Later among the works it cites.
Women also snowboard: Overcoming bias in captioning models
Kaylee Burns, Lisa Anne Hendricks, Trevor Darrell, and Anna Rohrbach · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited in the paper.
http://www.babynamewizard.com
Cited in the paper.