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Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains.
Interrater reliability: the kappa statistic
Mary L McHugh · 2012
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The socio-moral image database (smid): A novel stimulus set for the study of social, moral and affective processes
Damien L Crone, Stefan Bode, Carsten Murawski, and Simon M Laham · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
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Fairness and abstraction in sociotechnical systems
Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi · 2019
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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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Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation
Kimmo Karkkainen and Jungseock Joo · 2021
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Benchmark for compositional text-to-image synthesis
Dong Huk Park, Samaneh Azadi, Xihui Liu, Trevor Darrell, and Anna Rohrbach · 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, et al · 2021
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Dall·e 3
OpenAI · 2022
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Red-teaming the stable diffusion safety filter
Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, and Florian Tramèr · 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 L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Can machines help us answering question 16 in datasheets, and in turn reflecting on inappropriate content?
Patrick Schramowski, Christopher Tauchmann, and Kristian Kersting · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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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 · 2022
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Kandinsky 3.0 technical report
Vladimir Arkhipkin, Andrei Filatov, Viacheslav Vasilev, Anastasia Maltseva, Said Azizov, Igor Pavlov, Julia Agafonova, Andrey Kuznetsov, and Denis Dimitrov · 2023
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Surrogateprompt: Bypassing the safety filter of text-to-image models via substitution
Zhongjie Ba, Jieming Zhong, Jiachen Lei, Peng Cheng, Qinglong Wang, Zhan Qin, Zhibo Wang, and Kui Ren · 2023
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Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 2023
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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
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Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, and Aylin Caliskan · 2023
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Typology of risks of generative text-to-image models
Charlotte Bird, Eddie Ungless, and Atoosa Kasirzadeh · 2023
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Dall-eval: Probing the reasoning skills and social biases of text-to-image generation models
Jaemin Cho, Abhay Zala, and Mohit Bansal · 2023
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Erasing concepts from diffusion models
Rohit Gandikota, Joanna Materzyńska, Jaden Fiotto-Kaufman, and David Bau · 2023
Cited alongside, same era.
Facet: Fairness in computer vision evaluation benchmark
Laura Gustafson, Chloe Rolland, Nikhila Ravi, Quentin Duval, Aaron Adcock, Cheng-Yang Fu, Melissa Hall, and Candace Ross · 2023
Cited alongside, same era.
Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering
Yushi Hu, Benlin Liu, Jungo Kasai, Yizhong Wang, Mari Ostendorf, Ranjay Krishna, and Noah A Smith · 2023
Cited alongside, same era.
Llama guard: Llm-based input-output safeguard for human-ai conversations
Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al · 2023
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Camels in a changing climate: Enhancing lm adaptation with tulu 2
Hamish Ivison, Yizhong Wang, Valentina Pyatkin, Nathan Lambert, Matthew Peters, Pradeep Dasigi, Joel Jang, David Wadden, Noah A Smith, Iz Beltagy, et al · 2023
Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Unified concept editing in diffusion models
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau · 2024
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Generative ai prohibited use policy
Google · 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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Llavaguard: Vlm-based safeguards for vision dataset curation and safety assessment
Lukas Helff, Felix Friedrich, Manuel Brack, Kristian Kersting, and Patrick Schramowski · 2024
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Cited alongside, same era.
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 · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
Cited alongside, same era.
Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models
Yiting Qu, Xinyue Shen, Xinlei He, Michael Backes, Savvas Zannettou, and Yang Zhang · 2023
Cited alongside, same era.
Kandinsky: an improved text-to-image synthesis with image prior and latent diffusion
Anton Razzhigaev, Arseniy Shakhmatov, Anastasia Maltseva, Vladimir Arkhipkin, Igor Pavlov, Ilya Ryabov, Angelina Kuts, Alexander Panchenko, Andrey Kuznetsov, and Denis Dimitrov · 2023
Cited alongside, same era.
Adversarial diffusion distillation
Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach · 2023
Cited alongside, same era.
Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models
Patrick Schramowski, Manuel Brack, Björn Deiseroth, and Kristian Kersting · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al · 2024
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What matters when building vision-language models?
Hugo Laurençon, Léo Tronchon, Matthieu Cord, and Victor Sanh · 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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Llava-next: Improved reasoning, ocr, and world knowledge, 2024
Haotian Liu, Chunyuan Li, Yuheng Li, Bo Li, Yuanhan Zhang, Sheng Shen, and Yong Jae Lee · 2024
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Mace: Mass concept erasure in diffusion models
Shilin Lu, Zilan Wang, Leyang Li, Yanzhu Liu, and Adams Wai-Kin Kong · 2024
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Faintbench: A holistic and precise benchmark for bias evaluation in text-to-image models
Hanjun Luo, Ziye Deng, Ruizhe Chen, and Zuozhu Liu · 2024
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Terms of service
Midjourney · 2024
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Gpt-4o system card
OpenAI · 2024
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Usage policies
OpenAI · 2024
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Unsafebench: Benchmarking image safety classifiers on real-world and ai-generated images
Yiting Qu, Xinyue Shen, Yixin Wu, Michael Backes, Savvas Zannettou, and Yang Zhang · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
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Instantbooth: Personalized text-to-image generation without test-time finetuning
Jing Shi, Wei Xiong, Zhe Lin, and Hyun Joon Jung · 2024
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Dream studio terms of service
StabilityAI · 2024
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midjourney-prompts
Succinctly · 2024
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Vidprom: A million-scale real prompt-gallery dataset for text-to-video diffusion models
Wenhao Wang and Yi Yang · 2024
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Show-o: One single transformer to unify multimodal understanding and generation
Jinheng Xie, Weijia Mao, Zechen Bai, David Junhao Zhang, Weihao Wang, Kevin Qinghong Lin, Yuchao Gu, Zhijie Chen, Zhenheng Yang, and Mike Zheng Shou · 2024
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Sneakyprompt: Jailbreaking text-to-image generative models
Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao · 2024
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Mm-llms: Recent advances in multimodal large language models
Duzhen Zhang, Yahan Yu, Chenxing Li, Jiahua Dong, Dan Su, Chenhui Chu, and Dong Yu · 2024
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