Fetching the paper…
Reading the bibliography…
In recent years, word embeddings have been widely used to measure biases in texts.
Word association norms, mutual information, and lexicography
Kenneth Ward Church and Patrick Hanks. 1990 · 1990
Earlier work this paper cites.
Controlling the false discovery rate: A practical and powerful approach to multiple testing
Yoav Benjamini and Yosef Hochberg. 1995 · 1995
Earlier work this paper cites.
Bootstrap Methods and their Application
A. C. Davison and D. V. Hinkley. 1997 · 1997
Earlier work this paper cites.
A note on the calculation of empirical p values from monte carlo procedures
B. V. North, D. Curtis, and P. C. Sham. 2002 · 2002
Earlier work this paper cites.
Categorical data analysis , volume 482
Alan Agresti. 2003 · 2003
Earlier work this paper cites.
Speech and Language Processing (2nd Edition)
Daniel Jurafsky and James H. Martin. 2009 · 2009
Earlier work this paper cites.
Software Framework for Topic Modelling with Large Corpora
Radim Řehůřek and Petr Sojka. 2010 · 2010
Earlier work this paper cites.
Neural word embedding as implicit matrix factorization
Omer Levy and Yoav Goldberg. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Earlier work this paper cites.
Improving distributional similarity with lessons learned from word embeddings
Omer Levy, Yoav Goldberg, and Ido Dagan. 2015 · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
OpenSubtitles2016: Extracting large parallel corpora from movie and TV subtitles
Pierre Lison and Jörg Tiedemann. 2016 · 2016
Cited alongside, same era.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan. 2017 · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Corpus specificity in LSA and word2vec: The role of out-of-domain documents
Edgar Altszyler, Mariano Sigman, and Diego Fernández Slezak. 2018 · 2018
Cited alongside, same era.
Word embeddings quantify 100 years of gender and ethnic stereotypes
Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou. 2018 · 2018
Cited alongside, same era.
Second-order co-occurrence sensitivity of skip-gram with negative sampling
Dominik Schlechtweg, Cennet Oguz, and Sabine Schulte im Walde. 2019 · 2019
Later among the works it cites.
The Glasgow Norms: Ratings of 5,500 words on nine scales
Graham G Scott, Anne Keitel, Marc Becirspahic, Bo Yao, and Sara C Sereno. 2019 · 2019
Later among the works it cites.
How language shapes prejudice against women: An examination across 45 world languages
David DeFranza, Himanshu Mishra, and Arul Mishra. 2020 · 2020
Later among the works it cites.
Stereotypical gender associations in language have decreased over time
Jason J. Jones, Mohammad Ruhul Amin, Jessica Kim, and Steven Skiena. 2020 · 2020
Later among the works it cites.
Gender stereotypes are reflected in the distributional structure of 25 languages
Molly Lewis and Gary Lupyan. 2020 · 2020
Later among the works it cites.
Measuring model biases in the absence of ground truth
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Identifying and reducing gender bias in word-level language models
Shikha Bordia and Samuel R. Bowman. 2019 · 2019
Cited alongside, same era.
Understanding the origins of bias in word embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, and Richard Zemel. 2019 · 2019
Cited alongside, same era.
Understanding undesirable word embedding associations
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019 · 2019
Cited alongside, same era.
Half a century of stereotyping associations between gender and intellectual ability in films
Ramiro H. Gálvez, Valeria Tiffenberg, and Edgar Altszyler. 2019 · 2019
Cited alongside, same era.
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.
The geometry of culture: Analyzing the meanings of class through word embeddings
Austin C. Kozlowski, Matt Taddy, and James A. Evans. 2019 · 2019
Cited alongside, same era.
Osman Aka, Ken Burke, Alex Bauerle, Christina Greer, and Margaret Mitchell. 2021 · 2021
Closest in time.
Gender stereotypes in natural language: Word embeddings show robust consistency across child and adult language corpora of more than 65 million words
Tessa ES Charlesworth, Victor Yang, Thomas C Mann, Benedek Kurdi, and Mahzarin R Banaji. 2021 · 2021
Closest in time.
Measuring societal biases from text corpora with smoothed first-order co-occurrence
Navid Rekabsaz, Robert West, James Henderson, and Allan Hanbury. 2021 · 2021
Closest in time.
subs2vec: Word embeddings from subtitles in 55 languages
Jeroen van Paridon and Bill Thompson. 2021 · 2021
Closest in time.
The undesirable dependence on frequency of gender bias metrics based on word embeddings
Francisco Valentini, Germán Rosati, Diego Fernandez Slezak, and Edgar Altszyler. 2022 · 2022
Closest in time.