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As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks.
Victims of groupthink: A psychological study of foreign-policy decisions and fiascoes
Irving L Janis. 1972 · 1972
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Stereotype threat and the intellectual test performance of african americans
Claude M Steele and Joshua Aronson. 1995 · 1995
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Evolution of fred: Family responsibilities discrimination and developments in the law of stereotyping and implicit bias
Joan C Williams and Stephanie Bornstein. 2007 · 2007
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The weirdest people in the world?
Joseph Henrich, Steven J Heine, and Ara Norenzayan. 2010 · 2010
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Guilty by implicit racial bias: The guilty/not guilty implicit association test
Justin D Levinson, Huajian Cai, and Danielle Young. 2010 · 2010
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Explicit and implicit gender bias in workplace appraisals: How automatic prejudice affects decision making
Joel T Nadler. 2010 · 2010
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Implicit bias in the courtroom
Jerry Kang, Mark Bennett, Devon Carbado, Pam Casey, and Justin Levinson. 2011 · 2011
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Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities
Elizabeth N Chapman, Anna Kaatz, and Molly Carnes. 2013 · 2013
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Investors prefer entrepreneurial ventures pitched by attractive men
Alison Wood Brooks, Laura Huang, Sarah Wood Kearney, and Fiona E Murray. 2014 · 2014
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Addressing implicit bias, racial anxiety, and stereotype threat in education and health care
Rachel D Godsil, Linda R Tropp, Philip Atiba Goff, and John A Powell. 2014 · 2014
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Why it matters that student participation in maths and science is declining
R Wilson. 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 Zou, Venkatesh Saligrama, and Adam Kalai. 2016 · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, Eric Price, and Nati Srebro. 2016 · 2016
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Commercial content moderation: Digital laborers’ dirty work
Sarah T Roberts. 2016 · 2016
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Understanding implicit bias: What educators should know
Cheryl Staats. 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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Implicit bias in school disciplinary decisions
Gina Laura Gullo. 2017 · 2017
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Prejudice and politics re-examined the political significance of implicit racial bias
Donald R Kinder and Timothy J Ryan. 2017 · 2017
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The devil you don’t know: Implicit bias keeps women in their place
Michele N Struffolino. 2017 · 2017
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Minimizing and addressing implicit bias in the workplace: Be proactive, part one
Shamika Dalton and Michele Villagran. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. 2018 · 2018
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Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
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Mind the GAP: A balanced corpus of gendered ambiguous pronouns
Kellie Webster, Marta Recasens, Vera Axelrod, and Jason Baldridge. 2018 · 2018
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Technical boys and creative girls: the career aspirations of digitally skilled youths
Billy Wong and Peter EJ Kemp. 2018 · 2018
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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. 2018 · 2018
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Implicit bias
Michael Brownstein and Edward Zalta. 2019 · 2019
Towards mitigating LLM hallucination via self reflection
Ziwei Ji, Tiezheng Yu, Yan Xu, Nayeon Lee, Etsuko Ishii, and Pascale Fung. 2023 · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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Gender bias and stereotypes in large language models
Hadas Kotek, Rikker Dockum, and David Sun. 2023 · 2023
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Perspectives on the social impacts of reinforcement learning with human feedback
Gabrielle Kaili-May Liu. 2023 · 2023
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023
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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.
Gender bias in neural natural language processing
Kaiji Lu, Piotr Mardziel, Fangjing Wu, Preetam Amancharla, and Anupam Datta. 2019 · 2019
Cited alongside, same era.
The gender gap in stem fields: The impact of the gender stereotype of math and science on secondary students’ career aspirations
Elena Makarova, Belinda Aeschlimann, and Walter Herzog. 2019 · 2019
Cited alongside, same era.
On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019 · 2019
Cited alongside, same era.
The good, the bad, and the ugly of implicit bias
Cheryl Pritlove, Clara Juando-Prats, Kari Ala-Leppilampi, and Janet A Parsons. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
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Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. 2023 · 2023
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“kelly is a warm person, joseph is a role model”: Gender biases in LLM-generated reference letters
Yixin Wan, George Pu, Jiao Sun, Aparna Garimella, Kai-Wei Chang, and Nanyun Peng. 2023 · 2023
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Analyzing the impact of data selection and fine-tuning on economic and political biases in llms
Ahmed Agiza, Mohamed Mostagir, and Sherief Reda. 2024 · 2024
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Chateval: Towards better LLM-based evaluators through multi-agent debate
Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, and Zhiyuan Liu. 2024 · 2024
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Humans or llms as the judge? a study on judgement biases
Guiming Hardy Chen, Shunian Chen, Ziche Liu, Feng Jiang, and Benyou Wang. 2024 · 2024
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Reinforcement learning from multi-role debates as feedback for bias mitigation in llms
Ruoxi Cheng, Haoxuan Ma, Shuirong Cao, and Tianyu Shi. 2024 · 2024
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Bias runs deep: Implicit reasoning biases in persona-assigned LLMs
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, and Tushar Khot. 2024 · 2024
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Small language model can self-correct
Haixia Han, Jiaqing Liang, Jie Shi, Qianyu He, and Yanghua Xiao. 2024 · 2024
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Charles Koutcheme, Nicola Dainese, Sami Sarsa, Arto Hellas, Juho Leinonen, and Paul Denny. 2024 · 2024
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Steering LLMs towards unbiased responses: A causality-guided debiasing framework
Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, and Yang Liu. 2024 · 2024
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