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The importance of addressing fairness and bias in artificial intelligence (AI) systems cannot be over-emphasized.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Ctrl: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
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Fair-by-design explainable models for prediction of recidivism
Eduardo Soares and Plamen Angelov. 2019 · 1910
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Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting. 2023 · 1940
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RedditBias: A real-world resource for bias evaluation and debiasing of conversational language models
Soumya Barikeri, Anne Lauscher, Ivan Vulić, and Goran Glavaš. 2021 · 1955
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Equity theory revisited: Comments and annotated bibliography
J Stacy Adams and Sara Freedman. 1976 · 1976
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A method of assessing bias in test items
Janice Scheuneman. 1979 · 1979
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What should be done with equity theory? new approaches to the study of fairness in social relationships
Gerald S Leventhal. 1980 · 1980
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Organizational justice: Yesterday, today, and tomorrow
Jerald Greenberg. 1990 · 1990
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Objectification theory: Toward understanding women’s lived experiences and mental health risks
Barbara L Fredrickson and Tomi-Ann Roberts. 1997 · 1997
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Everyday sexism: Evidence for its incidence, nature, and psychological impact from three daily diary studies
Janet K Swim, Lauri L Hyers, Laurie L Cohen, and Melissa J Ferguson. 2001 · 2001
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Harvesting implicit group attitudes and beliefs from a demonstration web site
Brian A Nosek, Mahzarin R Banaji, and Anthony G Greenwald. 2002 · 2002
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Procedures for performing systematic reviews
Barbara Kitchenham. 2004 · 2004
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Lessons from applying the systematic literature review process within the software engineering domain
Pearl Brereton, Barbara A Kitchenham, David Budgen, Mark Turner, and Mohamed Khalil. 2007 · 2007
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Are gender-neutral queries really gender-neutral? mitigating gender bias in image search
Jialu Wang, Yang Liu, and Xin Wang. 2021 · 2008
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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, Ed Chi, and Slav Petrov. 2020 · 2010
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From women to objects: Appearance focus, target gender, and perceptions of warmth, morality and competence
Nathan A Heflick, Jamie L Goldenberg, Douglas P Cooper, and Elisa Puvia. 2011 · 2011
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2020b · 2012
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Multimodal neural language models
Ryan Kiros, Ruslan Salakhutdinov, and Rich Zemel. 2014 · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Differential validity and differential prediction of cognitive ability tests: Understanding test bias in the employment context
Christopher M Berry. 2015 · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
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The chicago face database: A free stimulus set of faces and norming data
Debbie S Ma, Joshua Correll, and Bernd Wittenbrink. 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 Y Zou, Venkatesh Saligrama, and Adam T Kalai. 2016 · 2016
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Multi30K: Multilingual English-German image descriptions
Desmond Elliott, Stella Frank, Khalil Sima’an, and Lucia Specia. 2016 · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Yfcc100m: The new data in multimedia research
Bart Thomee, David A Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li. 2016 · 2016
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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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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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017 · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi. 2017 · 2017
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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
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru. 2018 · 2018
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Voxceleb2: Deep speaker recognition
Joon Son Chung, Arsha Nagrani, and Andrew Zisserman. 2018 · 2018
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Fair generation through prior modification
Eric Frankel and Edward Vendrow. 2020 · 2018
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Reducing gender bias in abusive language detection
Ji Ho Park, Jamin Shin, and Pascale Fung. 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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Getting gender right in neural machine translation
Eva Vanmassenhove, Christian Hardmeier, and Andy Way. 2018 · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell. 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. 2018a · 2018
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Learning gender-neutral word embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, and Kai-Wei Chang. 2018b · 2018
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Now you see me, now you don’t: Detecting sexual objectification through a change blindness paradigm
Luca Andrighetto, Fabrizio Bracco, Carlo Chiorri, Michele Masini, Marcello Passarelli, and Tommaso Francesco Piccinno. 2019 · 2019
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Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
R. K. E. Bellamy, K. Dey, M. Hind, S. C. Hoffman, S. Houde, K. Kannan, P. Lohia, J. Martino, S. Mehta, A. Mojsilović, S. Nagar, K. Natesan Ramamurthy, J. Richards, D. Saha, P. Sattigeri, M. Singh, K. R. Varshney, and Y. Zhang. 2019 · 2019
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Understanding the origins of bias in word embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, and Richard Zemel. 2019 · 2019
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Attenuating bias in word vectors
Sunipa Dev and Jeff Phillips. 2019 · 2019
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Explaining models: an empirical study of how explanations impact fairness judgment
Jonathan Dodge, Q Vera Liao, Yunfeng Zhang, Rachel KE Bellamy, and Casey Dugan. 2019 · 2019
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Equalizing gender bias in neural machine translation with word embeddings techniques
Joel Escudé Font and Marta R. Costa-jussà. 2019 · 2019
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Understanding undesirable word embedding associations
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019 · 2019
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Academic plagiarism detection: a systematic literature review
Tomáš Foltỳnek, Norman Meuschke, and Bela Gipp. 2019 · 2019
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Counterfactual fairness in text classification through robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H Chi, and Alex Beutel. 2019 · 2019
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Parameter-efficient transfer learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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50 years of test (un) fairness: Lessons for machine learning
Ben Hutchinson and Margaret Mitchell. 2019 · 2019
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Measuring bias in contextualized word representations
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, and Yulia Tsvetkov. 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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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 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 · 2019
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Assessing social and intersectional biases in contextualized word representations
Yi Chern Tan and L Elisa Celis. 2019 · 2019
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Discriminating systems
Sarah Myers West, Meredith Whittaker, and Kate Crawford. 2019 · 2019
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Unlocking fairness: a trade-off revisited
Michael Wick, Jean-Baptiste Tristan, et al. 2019 · 2019
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A fairness-aware fusion framework for multimodal cyberbullying detection
Jamal Alasadi, Ramanathan Arunachalam, Pradeep K Atrey, and Vivek K Singh. 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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RobBERT: a Dutch RoBERTa-based Language Model
Pieter Delobelle, Thomas Winters, and Bettina Berendt. 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. 2020 · 2020
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CCAligned: A massive collection of cross-lingual web-document pairs
Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzmán, and Philipp Koehn. 2020 · 2020
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Explaining first impressions: Modeling, recognizing, and explaining apparent personality from videos
Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Gucluturk, Umut Güçlü, Xavier Baró, Isabelle Guyon, Julio Jacques Junior, Meysam Madadi, et al. 2020 · 2020
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Spatial biases in crowdsourced data: Social media content attention concentrates on populous areas in disasters
Chao Fan, Miguel Esparza, Jennifer Dargin, Fangsheng Wu, Bora Oztekin, and Ali Mostafavi. 2020 · 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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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. 2020a · 2020
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Social biases in NLP models as barriers for persons with disabilities
Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020 · 2020
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Privacy enhanced multimodal neural representations for emotion recognition
Mimansa Jaiswal and Emily Mower Provost. 2020 · 2020
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Lessons from archives: Strategies for collecting sociocultural data in machine learning
Eun Seo Jo and Timnit Gebru. 2020 · 2020
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Null-sampling for interpretable and fair representations
Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, and Novi Quadrianto. 2020 · 2020
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Cultural differences in bias? origin and gender bias in pre-trained german and french word embeddings
Mascha Kurpicz-Briki. 2020 · 2020
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Towards debiasing sentence representations
Paul Pu Liang, Irene Mengze Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, and Louis-Philippe Morency. 2020 · 2020
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Gender bias in neural natural language processing
Kaiji Lu, Piotr Mardziel, Fangjing Wu, Preetam Amancharla, and Anupam Datta. 2020 · 2020
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Hate speech detection and racial bias mitigation in social media based on bert model
Marzieh Mozafari, Reza Farahbakhsh, and Noël Crespi. 2020 · 2020
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Voxceleb: Large-scale speaker verification in the wild
Arsha Nagrani, Joon Son Chung, Weidi Xie, and Andrew Zisserman. 2020 · 2020
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Bias in data-driven artificial intelligence systems—an introductory survey
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, et al. 2020 · 2020
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Automatically neutralizing subjective bias in text
Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, and Diyi Yang. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Integrating multimodal information in large pretrained transformers
Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, Amir Zadeh, Chengfeng Mao, Louis-Philippe Morency, and Ehsan Hoque. 2020 · 2020
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Social bias frames: Reasoning about social and power implications of language
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, and Yejin Choi. 2020 · 2020
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Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 2020 · 2020
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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 · 2020
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Recast: Interactive auditing of automatic toxicity detection models
Austin P Wright, Omar Shaikh, Haekyu Park, Will Epperson, Muhammed Ahmed, Stephane Pinel, Diyi Yang, and Duen Horng Chau. 2020 · 2020
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Investigating bias and fairness in facial expression recognition
Tian Xu, Jennifer White, Sinan Kalkan, and Hatice Gunes. 2020 · 2020
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Mitigating biases in multimodal personality assessment
Shen Yan, Di Huang, and Mohammad Soleymani. 2020 · 2020
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Hurtful words: quantifying biases in clinical contextual word embeddings
Haoran Zhang, Amy X Lu, Mohamed Abdalla, Matthew McDermott, and Marzyeh Ghassemi. 2020 · 2020
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Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems
Agathe Balayn, Christoph Lofi, and Geert-Jan Houben. 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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Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe. 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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Bias and fairness in multimodal machine learning: A case study of automated video interviews
Brandon M Booth, Louis Hickman, Shree Krishna Subburaj, Louis Tay, Sang Eun Woo, and Sidney K D’Mello. 2021 · 2021
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HateBERT: Retraining BERT for abusive language detection in English
Tommaso Caselli, Valerio Basile, Jelena Mitrović, and Michael Granitzer. 2021 · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
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Could a conversational ai identify offensive language?
Daniela America da Silva, Henrique Duarte Borges Louro, Gildarcio Sousa Goncalves, Johnny Cardoso Marques, Luiz Alberto Vieira Dias, Adilson Marques da Cunha, and Paulo Marcelo Tasinaffo. 2021 · 2021
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Does gender matter in the news? detecting and examining gender bias in news articles
Jamell Dacon and Haochen Liu. 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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Bold: Dataset and metrics for measuring biases in open-ended language generation
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta. 2021 · 2021
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DebIE: A platform for implicit and explicit debiasing of word embedding spaces
Niklas Friedrich, Anne Lauscher, Simone Paolo Ponzetto, and Goran Glavaš. 2021 · 2021
Cited alongside, same era.
A survey on bias in deep nlp
Ismael Garrido-Muñoz, Arturo Montejo-Ráez, Fernando Martínez-Santiago, and L Alfonso Ureña-López. 2021 · 2021
Cited alongside, same era.
Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford. 2021 · 2021
Cited alongside, same era.
Mitigating demographic bias in facial datasets with style-based multi-attribute transfer
Markos Georgopoulos, James Oldfield, Mihalis A Nicolaou, Yannis Panagakis, and Maja Pantic. 2021 · 2021
Cited alongside, same era.
Detecting emergent intersectional biases: Contextualized word embeddings contain a distribution of human-like biases
Wei Guo and Aylin Caliskan. 2021 · 2021
Cited alongside, same era.
Dall-eval: Probing the reasoning skills and social biases of text-to-image generation models
Jaemin Cho, Abhay Zala, and Mohit Bansal. 2023 · 2023
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023 · 2023
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The future landscape of large language models in medicine
Jan Clusmann, Fiona R Kolbinger, Hannah Sophie Muti, Zunamys I Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Löffler, Sophie-Caroline Schwarzkopf, Michaela Unger, Gregory P Veldhuizen, et al. 2023 · 2023
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Large language models: A comprehensive exploration of modern ai’s potential and pitfalls
Bhavin Desai, Kapil Patil, Asit Patil, and Ishita Mehta. 2023 · 2023
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Improving gender-related fairness in sentence encoders: A semantics-based approach
Tommaso Dolci, Fabio Azzalini, and Mara Tanelli. 2023 · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Matan Halevy, Camille Harris, Amy Bruckman, Diyi Yang, and Ayanna Howard. 2021 · 2021
Cited alongside, same era.
Five sources of bias in natural language processing
Dirk Hovy and Shrimai Prabhumoye. 2021 · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig. 2021 · 2021
Cited alongside, same era.
How can we know when language models know? on the calibration of language models for question answering
Zhengbao Jiang, Jun Araki, Haibo Ding, and Graham Neubig. 2021 · 2021
Cited alongside, same era.
A review on explainability in multimodal deep neural nets
Gargi Joshi, Rahee Walambe, and Ketan Kotecha. 2021 · 2021
Cited alongside, same era.
Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation
Kimmo Karkkainen and Jungseock Joo. 2021 · 2021
Cited alongside, same era.
Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment
Karen Drukker, Weijie Chen, Judy Gichoya, Nicholas Gruszauskas, Jayashree Kalpathy-Cramer, Sanmi Koyejo, Kyle Myers, Rui C Sá, Berkman Sahiner, Heather Whitney, et al. 2023 · 2023
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Disambiguating algorithmic bias: from neutrality to justice
Elizabeth Edenberg and Alexandra Wood. 2023 · 2023
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Gpts are gpts: An early look at the labor market impact potential of large language models
Tyna Eloundou, Sam Manning, Pamela Mishkin, and Daniel Rock. 2023 · 2023
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ROBBIE: Robust bias evaluation of large generative language models
David Esiobu, Xiaoqing Tan, Saghar Hosseini, Megan Ung, Yuchen Zhang, Jude Fernandes, Jane Dwivedi-Yu, Eleonora Presani, Adina Williams, and Eric Smith. 2023 · 2023
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Improving gender fairness of pre-trained language models without catastrophic forgetting
Zahra Fatemi, Chen Xing, Wenhao Liu, and Caimming Xiong. 2023 · 2023
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WinoQueer: A community-in-the-loop benchmark for anti-LGBTQ+ bias in large language models
Virginia Felkner, Ho-Chun Herbert Chang, Eugene Jang, and Jonathan May. 2023 · 2023
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Fair diffusion: Instructing text-to-image generation models on fairness
Felix Friedrich, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Patrick Schramowski, Sasha Luccioni, and Kristian Kersting. 2023 · 2023
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" i wouldn’t say offensive but…": Disability-centered perspectives on large language models
Vinitha Gadiraju, Shaun Kane, Sunipa Dev, Alex Taylor, Ding Wang, Emily Denton, and Robin Brewer. 2023 · 2023
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Bias and fairness in large language models: A survey
Isabel O Gallegos, Ryan A Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K Ahmed. 2023 · 2023
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Datadoc analyzer: A tool for analyzing the documentation of scientific datasets
Joan Giner-Miguelez, Abel Gómez, and Jordi Cabot. 2023 · 2023
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Fairness evaluation within large language models through the lens of depression
Yuchen Han. 2023 · 2023
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Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine
Stefan Harrer. 2023 · 2023
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Look before you leap: An exploratory study of uncertainty measurement for large language models
Yuheng Huang, Jiayang Song, Zhijie Wang, Shengming Zhao, Huaming Chen, Felix Juefei-Xu, and Lei Ma. 2023 · 2023
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Mimic-iv, a freely accessible electronic health record dataset
Alistair EW Johnson, Lucas Bulgarelli, Lu Shen, Alvin Gayles, Ayad Shammout, Steven Horng, Tom J Pollard, Sicheng Hao, Benjamin Moody, Brian Gow, et al. 2023 · 2023
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Embracing large language models for medical applications: opportunities and challenges
Mert Karabacak and Konstantinos Margetis. 2023 · 2023
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Chatgpt for good? on opportunities and challenges of large language models for education
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, et al. 2023 · 2023
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Evaluating inclusivity, equity, and accessibility of nlp technology: A case study for indian languages
Simran Khanuja, Sebastian Ruder, and Partha Talukdar. 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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Parameter-efficient modularised bias mitigation via AdapterFusion
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, and Navid Rekabsaz. 2023 · 2023
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Auditing the ai auditors: A framework for evaluating fairness and bias in high stakes ai predictive models
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Bloom: A 176b-parameter open-access multilingual language model
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Holistic evaluation of text-to-image models
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Do we still need clinical language models?
Eric Lehman, Evan Hernandez, Diwakar Mahajan, Jonas Wulff, Micah J Smith, Zachary Ziegler, Daniel Nadler, Peter Szolovits, Alistair Johnson, and Emily Alsentzer. 2023 · 2023
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An investigation of structures responsible for gender bias in bert and distilbert
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Fairness-guided few-shot prompting for large language models
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Racial skew in fine-tuned legal ai language models
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Bias against 93 stigmatized groups in masked language models and downstream sentiment classification tasks
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The imperative for regulatory oversight of large language models (or generative ai) in healthcare
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Chatgpt and large language models in academia: opportunities and challenges
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Recent advances in natural language processing via large pre-trained language models: A survey
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Automating bias testing of llms
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Harnessing large language models in nursing care planning: opportunities, challenges, and ethical considerations
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Biases in large language models: origins, inventory, and discussion
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“i’m fully who i am”: Towards centering transgender and non-binary voices to measure biases in open language generation
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Bias and unfairness in machine learning models: a systematic review on datasets, tools, fairness metrics, and identification and mitigation methods
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Human-centric multimodal machine learning: Recent advances and testbed on ai-based recruitment
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Ethical challenges in the development of virtual assistants powered by large language models
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The casual conversations v2 dataset : A diverse, large benchmark for measuring fairness and robustness in audio/vision/speech models
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Fine-tuning aligned language models compromises safety, even when users do not intend to!
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True and fair: Robust and unbiased fake news detection via interpretable machine learning
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Fairness in language models beyond English: Gaps and challenges
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Chatgpt: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope
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A multi-dimensional study on bias in vision-language models
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The unequal opportunities of large language models: Examining demographic biases in job recommendations by chatgpt and llama
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A case study of fairness in generated images of large language models for software engineering tasks
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Whose opinions do language models reflect?
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Measuring fairness with biased data: A case study on the effects of unsupervised data in fairness evaluation
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Personality traits in large language models
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Dear: Debiasing vision-language models with additive residuals
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On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning
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Welcome to the era of chatgpt et al. the prospects of large language models
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Llama 2: Open foundation and fine-tuned chat models
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Contrastive language-vision ai models pretrained on web-scraped multimodal data exhibit sexual objectification bias
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Bias and fairness in chatbots: An overview
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End-to-end multimodal fact-checking and explanation generation: A challenging dataset and models
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Large language model as attributed training data generator: A tale of diversity and bias
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Vernacular? i barely know her: Challenges with style control and stereotyping
Ankit Aich, Tingting Liu, Salvatore Giorgi, Kelsey Isman, Lyle Ungar, and Brenda Curtis. 2024 · 2024
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Scaling implicit bias analysis across transformer-based language models through embedding association test and prompt engineering
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The dark side of dataset scaling: Evaluating racial classification in multimodal models
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Locating and mitigating gender bias in large language models
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A survey on evaluation of large language models
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Quantifying uncertainty in answers from any language model and enhancing their trustworthiness
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Mj-bench: Is your multimodal reward model really a good judge for text-to-image generation?
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Fairrefuse: Referee-guided fusion for multi-modal causal fairness in depression detection
Jiaee Cheong, Sinan Kalkan, and Hatice Gunes. 2024 · 2024
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Palm: scaling language modeling with pathways
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Reducing bias in sentiment analysis models through causal mediation analysis and targeted counterfactual training
Yifei Da, Matías Nicolás Bossa, Abel Díaz Berenguer, and Hichem Sahli. 2024 · 2024
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Fairness definitions in language models explained
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Fairness certification for natural language processing and large language models
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Datacomp: In search of the next generation of multimodal datasets
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Evaluation and mitigation of the limitations of large language models in clinical decision-making
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The ethics of chatgpt in medicine and healthcare: a systematic review on large language models (llms)
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Transforming assessment: The impacts and implications of large language models and generative ai
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Bias mitigation for machine learning classifiers: A comprehensive survey
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Large language models are zero-shot rankers for recommender systems
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Equity and fairness challenges in online learning in the age of chatgpt
Hasan Jamil. 2024 · 2024
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Communicating the cultural other: Trust and bias in generative ai and large language models
Christopher J Jenks. 2024 · 2024
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Feature-based text search engine mitigating data diversity problem using pre-trained large language model for fast deployment services
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Beavertails: Towards improved safety alignment of llm via a human-preference dataset
Jiaming Ji, Mickel Liu, Josef Dai, Xuehai Pan, Chi Zhang, Ce Bian, Boyuan Chen, Ruiyang Sun, Yizhou Wang, and Yaodong Yang. 2024 · 2024
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Generating images with multimodal language models
Jing Yu Koh, Daniel Fried, and Russ R Salakhutdinov. 2024 · 2024
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Bias and cyberbullying detection and data generation with transformer ai models and top llms
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The life cycle of large language models in education: A framework for understanding sources of bias
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Probing into the fairness of large language models: A case study of chatgpt
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Leveraging diffusion perturbations for measuring fairness in computer vision
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Foundation and large language models: fundamentals, challenges, opportunities, and social impacts
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Large language models in healthcare and medical domain: A review
Zabir Al Nazi and Wei Peng. 2024 · 2024
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Langtest: A comprehensive evaluation library for custom llm and nlp models
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Irene Pagliai, Goya van Boven, Tosin Adewumi, Lama Alkhaled, Namrata Gurung, Isabella Södergren, and Elisa Barney. 2024 · 2024
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Generative ai and teachers–for us or against us? a case study
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Fair enough: Develop and assess a fair-compliant dataset for large language model training?
Shaina Raza, Shardul Ghuge, Chen Ding, Elham Dolatabadi, and Deval Pandya. 2024 · 2024
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Fairsna: Algorithmic fairness in social network analysis
Akrati Saxena, George Fletcher, and Mykola Pechenizkiy. 2024 · 2024
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Are emergent abilities of large language models a mirage?
Rylan Schaeffer, Brando Miranda, and Sanmi Koyejo. 2024 · 2024
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On measuring fairness in generative models
Christopher Teo, Milad Abdollahzadeh, and Ngai-Man Man Cheung. 2024 · 2024
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Undesirable biases in nlp: Addressing challenges of measurement
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Ceb: Compositional evaluation benchmark for fairness in large language models
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Invisible relevance bias: Text-image retrieval models prefer ai-generated images
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Fairness-aware structured pruning in transformers
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, and Sarath Chandar. 2024 · 2024
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MM-LLMs: Recent advances in MultiModal large language models
Duzhen Zhang, Yahan Yu, Jiahua Dong, Chenxing Li, Dan Su, Chenhui Chu, and Dong Yu. 2024a · 2024
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Can large language models transform computational social science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang. 2024 · 2024
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BBQ: A hand-built bias benchmark for question answering
Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, and Samuel Bowman. 2022 · 2086
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