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Machine learning models have been shown to inherit biases from their training datasets.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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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
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper 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
Earlier work this paper cites.
Turning a blind eye: Explicit removal of biases and variation from deep neural network embeddings
Mohsan Alvi, Andrew Zisserman, and Christoffer Nellåker · 2018
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Word embeddings quantify 100 years of gender and ethnic stereotypes
Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou · 2018
Earlier work this paper cites.
Learning adversarially fair and transferable representations
David Madras, Elliot Creager, Toniann Pitassi, and Richard Zemel · 2018
Earlier work this paper cites.
Fairgan: Fairness-aware generative adversarial networks
Depeng Xu, Shuhan Yuan, Lu Zhang, and Xintao Wu · 2018
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Fairness-aware ranking in search & recommendation systems with application to linkedin talent search
Sahin Cem Geyik, Stuart Ambler, and Krishnaram Kenthapadi · 2019
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Hila Gonen and Yoav Goldberg · 2019
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Bias correction of learned generative models using likelihood-free importance weighting
Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric J Horvitz, and Stefano Ermon · 2019
Earlier work this paper cites.
Reducing sentiment bias in language models via counterfactual evaluation
Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, and Pushmeet Kohli · 2019
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Fairface: Face attribute dataset for balanced race, gender, and age
Kimmo Kärkkäinen and Jungseock Joo · 2019
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Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov, and Alan W Black · 2019
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Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 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
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Racial faces in the wild: Reducing racial bias by information maximization adaptation network
Mei Wang, Weihong Deng, Jiani Hu, Xunqiang Tao, and Yaohai Huang · 2019
Earlier work this paper cites.
Gender bias in contextualized word embeddings
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, and Kai-Wei Chang · 2019
Cited alongside, same era.
Language (technology) is power: A critical survey of" bias" in nlp
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach · 2020
Cited alongside, same era.
Fair generative modeling via weak supervision
Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, and Stefano Ermon · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al · 2021
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A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning
Hugo Berg, Siobhan Mackenzie Hall, Yash Bhalgat, Wonsuk Yang, Hannah Rose Kirk, Aleksandar Shtedritski, and Max Bain · 2022
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Dall-eval: Probing the reasoning skills and social biases of text-to-image generative transformers
Jaemin Cho, Abhay Zala, and Mohit Bansal · 2022
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On feature learning in the presence of spurious correlations
Pavel Izmailov, Polina Kirichenko, Nate Gruver, and Andrew Gordon Wilson · 2022
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Paul Pu Liang, Irene Mengze Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, and Louis-Philippe Morency · 2020
Cited alongside, same era.
Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy · 2020
Cited alongside, same era.
Mitigating bias in face recognition using skewness-aware reinforcement learning
Mei Wang and Weihong Deng · 2020
Cited alongside, same era.
Towards fairness in visual recognition: Effective strategies for bias mitigation
Zeyu Wang, Klint Qinami, Ioannis Christos Karakozis, Kyle Genova, Prem Nair, Kenji Hata, and Olga Russakovsky · 2020
Cited alongside, same era.
Evaluating clip: towards characterization of broader capabilities and downstream implications
Sandhini Agarwal, Gretchen Krueger, Jack Clark, Alec Radford, Jong Wook Kim, and Miles Brundage · 2021
Cited alongside, same era.
Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe · 2021
Cited alongside, same era.
Fair mixup: Fairness via interpolation
Ching-Yao Chuang and Youssef Mroueh · 2021
Cited alongside, same era.
Clip-adapter: Better vision-language models with feature adapters
Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, and Yu Qiao · 2021
Cited alongside, same era.
Polina Kirichenko, Pavel Izmailov, and Andrew Gordon Wilson · 2022
Later among the works it cites.
Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Jones, Tengyu Ma, and Percy Liang · 2022
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Dall· e 2 preview-risks and limitations
P Mishkin, L Ahmad, M Brundage, G Krueger, and G Sastry · 2022
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Debiasing methods for fairer neural models in vision and language research: A survey
Otávio Parraga, Martin D More, Christian M Oliveira, Nathan S Gavenski, Lucas S Kupssinskü, Adilson Medronha, Luis V Moura, Gabriel S Simões, and Rodrigo C Barros · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, et al · 2022
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Contrastive adapters for foundation model group robustness
Michael Zhang and Christopher Ré · 2022
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Fair diffusion: Instructing text-to-image generation models on fairness
Felix Friedrich, Patrick Schramowski, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Sasha Luccioni, and Kristian Kersting · 2023
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Vision-language models performing zero-shot tasks exhibit gender-based disparities
Melissa Hall, Laura Gustafson, Aaron Adcock, Ishan Misra, and Candace Ross · 2023
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Gpt-4 technical report
OpenAI · 2023
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Dear: Debiasing vision-language models with additive residuals
Ashish Seth, Mayur Hemani, and Chirag Agarwal · 2023
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