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The recent advancement of large and powerful models with Text-to-Image (T2I) generation abilities -- such as OpenAI's DALLE-3 and Google's Gemini -- enables users to generate high-quality images from textual prompts.
Generic masculine words and thinking
Jeanette Silveira · 1980
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Skin colour typology and suntanning pathways
Alain Chardon, Isabelle Cretois, and Colette Hourseau · 1991
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Face recognition performance: Role of demographic information
Brendan F. Klare, Mark J. Burge, Joshua C. Klontz, Richard W. Vorder Bruegge, and Anil K. Jain · 2012
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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
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Deepface: Closing the gap to human-level performance in face verification
Yaniv Taigman, Ming Yang, Marc’Aurelio Ranzato, and Lior Wolf · 2014
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Dex: Deep expectation of apparent age from a single image
Rasmus Rothe, Radu Timofte, and Luc Van Gool · 2015
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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The problem with bias: Allocative versus representational harms in machine learning
Solon Barocas, Kate Crawford, Aaron Shapiro, and Hanna Wallach · 2017
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How far are we from solving the 2d & 3d face alignment problem?(and a dataset of 230,000 3d facial landmarks)
Adrian Bulat and Georgios Tzimiropoulos · 2017
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan · 2017
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The trouble with bias
Kate Crawford · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Review on the effects of age, gender, and race demographics on automatic face recognition
Salem Hamed Abdurrahim, Salina Abdul Samad, and Aqilah Baseri Huddin · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Understanding unequal gender classification accuracy from face images, 2018
Vidya Muthukumar, Tejaswini Pedapati, Nalini Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, and Kush R. Varshney · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
R. Zhang, P. Isola, A. A. Efros, E. Shechtman, and O. Wang · 2018
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 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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Characterizing bias in classifiers using generative models
Daniel McDuff, Shuang Ma, Yale Song, and Ashish Kapoor · 2019
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Modeling human annotation errors to design bias-aware systems for social stream processing
Rahul Pandey, Carlos Castillo, and Hemant Purohit · 2019
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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
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Retinaface: Single-shot multi-level face localisation in the wild
Jiankang Deng, Jia Guo, Evangelos Ververas, Irene Kotsia, and Stefanos Zafeiriou · 2020
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Understanding fairness of gender classification algorithms across gender-race groups
Anoop Krishnan, Ali Almadan, and Ajita Rattani · 2020
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Diversity and inclusion metrics in subset selection
Margaret Mitchell, Dylan Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, and Jamie Morgenstern · 2020
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Gender classification and bias mitigation in facial images
Wenying Wu, Pavlos Protopapas, Zheng Yang, and Panagiotis Michalatos · 2020
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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
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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How well can text-to-image generative models understand ethical natural language interventions?
Hritik Bansal, Da Yin, Masoud Monajatipoor, and Kai-Wei Chang · 2022
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Analyzing the effects of annotator gender across NLP tasks
Laura Biester, Vanita Sharma, Ashkan Kazemi, Naihao Deng, Steven Wilson, and Rada Mihalcea · 2022
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Towards racially unbiased skin tone estimation via scene disambiguation
Haiwen Feng, Timo Bolkart, Joachim Tesch, Michael J Black, and Victoria Abrevaya · 2022
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Improving skin tone evaluation in machine learning
Google Responsible AI · 2022
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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 · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Deep generative views to mitigate gender classification bias across gender-race groups
Sreeraj Ramachandran and Ajita Rattani · 2022
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Annotators with attitudes: How annotator beliefs and identities bias toxic language detection
Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi, and Noah A. Smith · 2022
Cited alongside, same era.
Unified detoxifying and debiasing in language generation via inference-time adaptive optimization
Zonghan Yang, Xiaoyuan Yi, Peng Li, Yang Liu, and Xing Xie · 2022
How ai-assisted rpg tales of syn utilizes stable diffusion and chatgpt to create assets and dialogues
Evgeny Obedkov · 2023
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Dall·e 3 system card, Oct 2023
OpenAI · 2023
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Editing implicit assumptions in text-to-image diffusion models
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov · 2023
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“i’m fully who i am”: Towards centering transgender and non-binary voices to measure biases in open language generation
Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard Zemel, and Rahul Gupta · 2023
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Factoring the matrix of domination: A critical review and reimagination of intersectionality in ai fairness
Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee, and Kai-Wei Chang · 2023
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Cited alongside, same era.
Hrs-bench: Holistic, reliable and scalable benchmark for text-to-image models
Eslam Mohamed Bakr, Pengzhan Sun, Xiaogian Shen, Faizan Farooq Khan, Li Erran Li, and Mohamed Elhoseiny · 2023
Cited alongside, same era.
Peering through preferences: Unraveling feedback acquisition for aligning large language models
Hritik Bansal, John Dang, and Aditya Grover · 2023
Cited alongside, same era.
Inspecting the geographical representativeness of images from text-to-image models
Abhipsa Basu, R Venkatesh Babu, and Danish Pruthi · 2023
Cited alongside, same era.
Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Mira Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan, et al · 2023
Cited alongside, same era.
Typology of risks of generative text-to-image models
Charlotte Bird, Eddie Ungless, and Atoosa Kasirzadeh · 2023
Cited alongside, same era.
Open problems and fundamental limitations of reinforcement learning from human feedback
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, et al · 2023
Cited alongside, same era.
Minigpt-v2: large language model as a unified interface for vision-language multi-task learning, 2023
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, and Mohamed Elhoseiny · 2023
Cited alongside, same era.
Gaussian harmony: Attaining fairness in diffusion-based face generation models, 2023
Basudha Pal, Arunkumar Kannan, Ram Prabhakar Kathirvel, Alice J. O’Toole, and Rama Chellappa · 2023
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Ai’s regimes of representation: A community-centered study of text-to-image models in south asia
Rida Qadri, Renee Shelby, Cynthia L. Bennett, and Emily Denton · 2023
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A multi-dimensional study on bias in vision-language models
Gabriele Ruggeri and Debora Nozza · 2023
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Nlpositionality: Characterizing design biases of datasets and models
Sebastin Santy, Jenny T Liang, Ronan Le Bras, Katharina Reinecke, and Maarten Sap · 2023
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The bias amplification paradox in text-to-image generation, 2023
Preethi Seshadri, Sameer Singh, and Yanai Elazar · 2023
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Finetuning text-to-image diffusion models for fairness
Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, and Mohan Kankanhalli · 2023
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Evaluating the social impact of generative ai systems in systems and society, 2023
Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan Baker, Su Lin Blodgett, Hal Daumé III au2, Jesse Dodge, Ellie Evans, Sara Hooker, Yacine Jernite, Alexandra Sasha Luccioni, Alberto Lusoli, Margaret Mitchell, Jessica Newman, Marie-Therese Png, Andrew Strait, and Apostol Vassilev · 2023
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Exploiting cultural biases via homoglyphs in text-to-image synthesis
Lukas Struppek, Dom Hintersdorf, Felix Friedrich, Patrick Schramowski, Kristian Kersting, et al · 2023
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Dreamsync: Aligning text-to-image generation with image understanding feedback
Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Stereotypes and smut: The (mis)representation of non-cisgender identities by text-to-image models
Eddie Ungless, Bjorn Ross, and Anne Lauscher · 2023
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Quantifying bias in text-to-image generative models, 2023
Jordan Vice, Naveed Akhtar, Richard Hartley, and Ajmal Mian · 2023
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Diffusion model alignment using direct preference optimization
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, and Nikhil Naik · 2023
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T2IAT: Measuring valence and stereotypical biases in text-to-image generation
Jialu Wang, Xinyue Liu, Zonglin Di, Yang Liu, and Xin Wang · 2023
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DiffusionDB: A large-scale prompt gallery dataset for text-to-image generative models
Zijie J. Wang, Evan Montoya, David Munechika, Haoyang Yang, Benjamin Hoover, and Duen Horng Chau · 2023
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Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, and Hongsheng Li · 2023
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Diverse diffusion: Enhancing image diversity in text-to-image generation, 2023
Mariia Zameshina, Olivier Teytaud, and Laurent Najman · 2023
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Reinforcement learning for fine-tuning text-to-image diffusion models
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee · 2024
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Multilingual text-to-image generation magnifies gender stereotypes and prompt engineering may not help you
Felix Friedrich, Katharina Hämmerl, Patrick Schramowski, Jindrich Libovicky, Kristian Kersting, and Alexander Fraser · 2024
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Harm amplification in text-to-image models
Susan Hao, Renee Shelby, Yuchi Liu, Hansa Srinivasan, Mukul Bhutani, Burcu Karagol Ayan, Shivani Poddar, and Sarah Laszlo · 2024
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Debiasing text-to-image diffusion models, 2024
Ruifei He, Chuhui Xue, Haoru Tan, Wenqing Zhang, Yingchen Yu, Song Bai, and Xiaojuan Qi · 2024
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Beyond the surface: A global-scale analysis of visual stereotypes in text-to-image generation
Akshita Jha, Vinodkumar Prabhakaran, Remi Denton, Sarah Laszlo, Shachi Dave, Rida Qadri, Chandan K. Reddy, and Sunipa Dev · 2024
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Pick-a-pic: An open dataset of user preferences for text-to-image generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2024
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Holistic evaluation of text-to-image models
Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Teufel, Marco Bellagente, et al · 2024
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Scoft: Self-contrastive fine-tuning for equitable image generation
Zhixuan Liu, Peter Schaldenbrand, Beverley-Claire Okogwu, Wenxuan Peng, Youngsik Yun, Andrew Hundt, Jihie Kim, and Jean Oh · 2024
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Ethical AI Isn’t to Blame for Google’s Gemini Debacle — time.com
Margaret Mitchell · 2024
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A unified framework and dataset for assessing gender bias in vision-language models, 2024
Ashutosh Sathe, Prachi Jain, and Sunayana Sitaram · 2024
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Yixin Wan and Kai-Wei Chang · 2024
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Imagereward: Learning and evaluating human preferences for text-to-image generation
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2024
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