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All AI models are susceptible to learning biases in data that they are trained on.
The second conversational intelligence challenge (ConvAI2)
Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander H. Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander I. Rudnicky, Jason Williams, Joelle Pineau, Mikhail S. Burtsev, and Jason Weston. 2019 · 1902
Earlier work this paper cites.
Neural text generation with unlikelihood training
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston. 2019a · 1908
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Acute-eval: Improved dialogue evaluation with optimized questions and multi-turn comparisons
Margaret Li, Jason Weston, and Stephen Roller. 2019 · 1909
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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On the measure of concentration with special reference to income and statistics
Corrado Gini. 1936 · 1936
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CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
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First-name stereotypes as a factor in self-concept and school achievement
S Gray Garwood. 1976 · 1976
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First-name stereotypes and expected academic achievement of students
Susan D Nelson. 1977 · 1977
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Women, race, & class
Angela Y Davis. 1981 · 1981
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Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics
Kimberle Crenshaw. 1989 · 1989
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Gender trouble: Feminism and the subversion of identity
Judith Butler. 1990 · 1990
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Language in thought and action
Samuel Ichiyé Hayakawa and Alan R Hayakawa. 1990 · 1990
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Measuring sex stereotypes: A multination study, (Rev. Ed.)
John E Williams and Deborah L Best. 1990 · 1990
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Distinctive african american names: An experimental, historical, and linguistic analysis of innovation
Stanley Lieberson and Kelly S Mikelson. 1995 · 1995
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Automatic preference for white americans: Eliminating the familiarity explanation
Nilanjana Dasgupta, Debbie E McGhee, Anthony G Greenwald, and Mahzarin R Banaji. 2000 · 2000
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A matter of taste: How names, fashions, and culture change
Stanley Lieberson. 2000 · 2000
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Why susie sells seashells by the seashore: implicit egotism and major life decisions
Brett W Pelham, Matthew C Mirenberg, and John T Jones. 2002 · 2002
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Are Emily and Greg more employable than Lakisha and Jamal? a field experiment on labor market discrimination
Marianne Bertrand and Sendhil Mullainathan. 2004 · 2004
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Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2004
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Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M Smith, et al. 2020 · 2004
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Names, expectations and the black-white test score gap
David N Figlio. 2005 · 2005
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Wei Guo and Aylin Caliskan. 2020 · 2006
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Fitting in or standing out: Trends in american parents’ choices for children’s names, 1880–2007
Jean M Twenge, Emodish M Abebe, and W Keith Campbell. 2010 · 2007
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Controlling style in generated dialogue
Eric Michael Smith, Diana Gonzalez-Rico, Emily Dinan, and Y-Lan Boureau. 2020a · 2009
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Racial and gender differences in diversity of first names
Herbert Barry III and Aylene S Harper. 2010 · 2010
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Characterising bias in compressed models
Sara Hooker, Nyalleng Moorosi, Gregory Clark, Samy Bengio, and Emily Denton. 2020 · 2010
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Pre-trained summarization distillation
Sam Shleifer and Alexander M Rush. 2020 · 2010
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Measuring and reducing gendered correlations in pre-trained models
Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, and Slav Petrov. 2020 · 2010
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Recipes for safety in open-domain chatbots
Jing Xu, Da Ju, Margaret Li, Y-Lan Boureau, Jason Weston, and Emily Dinan. 2020 · 2010
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“selling the farm to buy the cow” the narrativized consequences of “black names” from within the african american community
Ayanna F Brown and Janice Tuck Lively. 2012 · 2012
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Heterogeneity in discrimination?: A field experiment
Katherine L Milkman, Modupe Akinola, and Dolly Chugh. 2012 · 2012
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Sex differences in social behavior: A social-role interpretation
Alice H Eagly. 2013 · 2013
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The nature of social dominance orientation: Theorizing and measuring preferences for intergroup inequality using the new sdo7 scale
Arnold K Ho, Jim Sidanius, Nour Kteily, Jennifer Sheehy-Skeffington, Felicia Pratto, Kristin E Henkel, Rob Foels, and Andrew L Stewart. 2015 · 2015
Cited alongside, same era.
Naming ourselves and others
Marıa S Rivera Maulucci and Felicia Moore Mensah. 2015 · 2015
Cited alongside, same era.
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
Cited alongside, same era.
Stereotypes about gender and science: Women ≠ \neq scientists
Linda L Carli, Laila Alawa, YoonAh Lee, Bei Zhao, and Elaine Kim. 2016 · 2016
Cited alongside, same era.
Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao. 2016 · 2016
Cited alongside, same era.
It’s all in the name: Mitigating gender bias with name-based counterfactual data substitution
Rowan Hall Maudslay, Hila Gonen, Ryan Cotterell, and Simone Teufel. 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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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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What’s in a name? Reducing bias in bios without access to protected attributes
Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Anna Rumshisky, and Adam Kalai. 2019 · 2019
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Evaluating gender bias in machine translation
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019 · 2019
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Two short “as” and a rolling “r” autoethnographic reflections on a “difficult” name
Sara Louise Wheeler. 2016 · 2016
Cited alongside, same era.
Socio-onomastics: The pragmatics of names , volume 275
Terhi Ainiala and Jan-Ola Östman. 2017 · 2017
Cited alongside, same era.
Singular they and the syntactic representation of gender in english
Bronwyn M. Bjorkman. 2017 · 2017
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.
Names before pronouns: Variation in pronominal reference and gender
Kirby Conrod. 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.
Data statements for natural language processing: Toward mitigating system bias and enabling better science
Emily M. Bender and Batya Friedman. 2018 · 2018
Cited alongside, same era.
Assessing social and intersectional biases in contextualized word representations
Yi Chern Tan and L. Elisa Celis. 2019 · 2019
Later among the works it cites.
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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The pushshift reddit dataset
Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, and Jeremy Blackburn. 2020 · 2020
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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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Pronouns and gender in language
Kirby Conrod. 2020 · 2020
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Queens are powerful too: Mitigating gender bias in dialogue generation
Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, and Jason Weston. 2020a · 2020
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Multi-dimensional gender bias classification
Emily Dinan, Angela Fan, Ledell Wu, Jason Weston, Douwe Kiela, and Adina Williams. 2020b · 2020
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RealToxicityPrompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 2020 · 2020
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Black names, immigrant names: Navigating race and ethnicity through personal names
Hewan Girma. 2020 · 2020
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Type B reflexivization as an unambiguous testbed for multilingual multi-task gender bias
Ana Valeria González, Maria Barrett, Rasmus Hvingelby, Kellie Webster, and Anders Søgaard. 2020 · 2020
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Tinybert: Distilling bert for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020 · 2020
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Don’t say that! making inconsistent dialogue unlikely with unlikelihood training
Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, and Jason Weston. 2020 · 2020
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Mitigating gender bias for neural dialogue generation with adversarial learning
Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, and Jiliang Tang. 2020b · 2020
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Demographic stability on mechanical turk despite covid-19
Aaron J Moss, Cheskie Rosenzweig, Jonathan Robinson, and Leib Litman. 2020 · 2020
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Assessing gender bias in machine translation: a case study with google translate
Marcelo O. R. Prates, Pedro H. C. Avelar, and Luís C. Lamb. 2020 · 2020
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Dialogpt: Large-scale generative pre-training for conversational response generation
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and William B Dolan. 2020 · 2020
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Soumya Barikeri, Anne Lauscher, Ivan Vulić, and Goran Glavaš. 2021 · 2021
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On the dangers of stochastic parrots: Can language models be too big?
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Stereotyping norwegian salmon: An inventory of pitfalls in fairness benchmark datasets
Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, and Hanna Wallach. 2021 · 2021
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A survey of race, racism, and anti-racism in nlp
Anjalie Field, Su Lin Blodgett, Zeerak Waseem, and Yulia Tsvetkov. 2021 · 2021
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Gender bias amplification during speed-quality optimization in neural machine translation
Adithya Renduchintala, Denise Diaz, Kenneth Heafield, Xian Li, and Mona Diab. 2021 · 2021
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Investigating failures of automatic translation in the case of unambiguous gender
Adithya Renduchintala and Adina Williams. 2021 · 2021
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Gender bias in machine translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021 · 2021
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Revealing persona biases in dialogue systems
Emily Sheng, Josh Arnold, Zhou Yu, Kai-Wei Chang, and Nanyun Peng. 2021 · 2021
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Stereotype and skew: Quantifying gender bias in pre-trained and fine-tuned language models
Daniel de Vassimon Manela, David Errington, Thomas Fisher, Boris van Breugel, and Pasquale Minervini. 2021 · 2021
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Can you put it all together: Evaluating conversational agents’ ability to blend skills
Eric Michael Smith, Mary Williamson, Kurt Shuster, Jason Weston, and Y-Lan Boureau. 2020b · 2030
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