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Text-to-image (T2I) diffusion models (DMs) have shown promise in generating high-quality images from textual descriptions.
Im2text: Describing images using 1 million captioned photographs
Vicente Ordonez, Girish Kulkarni, and Tamara Berg · 2011
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, and Rob Fergus · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Training generative neural networks via maximum mean discrepancy optimization
Gintare Karolina Dziugaite, Daniel M Roy, and Zoubin Ghahramani · 2015
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Minimax estimation of maximum mean discrepancy with radial kernels
Ilya O Tolstikhin, Bharath K Sriperumbudur, and Bernhard Schölkopf · 2016
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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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Textbugger: Generating adversarial text against real-world applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang · 2018
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Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, et al · 2018
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Pathologies of neural models make interpretations difficult
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber · 2018
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Text processing like humans do: Visually attacking and shielding nlp systems
Steffen Eger, Gözde Gül Şahin, Andreas Rücklé, Ji-Ung Lee, Claudia Schulz, Mohsen Mesgar, Krishnkant Swarnkar, Edwin Simpson, and Iryna Gurevych · 2019
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Text processing like humans do: Visually attacking and shielding nlp systems
Steffen Eger, Gözde Gül Şahin, Andreas Rücklé, Ji-Ung Lee, Claudia Schulz, Mohsen Mesgar, Krishnkant Swarnkar, Edwin Simpson, and Iryna Gurevych · 2019
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Universal adversarial triggers for attacking and analyzing nlp
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh · 2019
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Combating adversarial misspellings with robust word recognition
Danish Pruthi, Bhuwan Dhingra, and Zachary C Lipton · 2019
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Universal adversarial attacks on text classifiers
Melika Behjati, Seyed-Mohsen Moosavi-Dezfooli, Mahdieh Soleymani Baghshah, and Pascal Frossard · 2019
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Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Evading deepfake-image detectors with white-and black-box attacks
Nicholas Carlini and Hany Farid · 2020
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From hero to zéroe: A benchmark of low-level adversarial attacks
Steffen Eger and Yannik Benz · 2020
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Adversarial attacks on deep-learning models in natural language processing: A survey
Wei Emma Zhang, Quan Z Sheng, Ahoud Alhazmi, and Chenliang Li · 2020
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A geometry-inspired attack for generating natural language adversarial examples
Zhao Meng and Roger Wattenhofer · 2020
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T3: Tree-autoencoder constrained adversarial text generation for targeted attack
Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, and Bo Li · 2020
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Adversarial attack and defense of structured prediction models
Wenjuan Han, Liwen Zhang, Yong Jiang, and Kewei Tu · 2020
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BERT-ATTACK: adversarial attack against BERT using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu · 2020
Cited alongside, same era.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Cited alongside, same era.
Cogview: Mastering text-to-image generation via transformers
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, et al · 2021
Adversarial attacks on image generation with made-up words
Raphaël Millière · 2022
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Thai Le, Jooyoung Lee, Kevin Yen, Yifan Hu, and Dongwon Lee · 2022
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Make-a-scene: Scene-based text-to-image generation with human priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
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What the daam: Interpreting stable diffusion using cross attention
Raphael Tang, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Jimmy Lin, and Ferhan Ture · 2022
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Pretraining is all you need for image-to-image translation
Tengfei Wang, Ting Zhang, Bo Zhang, Hao Ouyang, Dong Chen, Qifeng Chen, and Fang Wen · 2022
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Cited alongside, same era.
Model extraction and adversarial transferability, your bert is vulnerable!
Xuanli He, Lingjuan Lyu, Lichao Sun, and Qiongkai Xu · 2021
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Contextualized perturbation for textual adversarial attack
Dianqi Li, Yizhe Zhang, Hao Peng, Liqun Chen, Chris Brockett, Ming-Ting Sun, and William B Dolan · 2021
Cited alongside, same era.
Synthesizing adversarial negative responses for robust response ranking and evaluation
Prakhar Gupta, Yulia Tsvetkov, and Jeffrey P Bigham · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
Cited alongside, same era.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
Cited alongside, same era.
Later among the works it cites.
Sketch-guided text-to-image diffusion models
Andrey Voynov, Kfir Aberman, and Daniel Cohen-Or · 2022
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Investigating top-k white-box and transferable black-box attack
Chaoning Zhang, Philipp Benz, Adil Karjauv, Jae Won Cho, Kang Zhang, and In So Kweon · 2022
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Exploring the universal vulnerability of prompt-based learning paradigm
Lei Xu, Yangyi Chen, Ganqu Cui, Hongcheng Gao, and Zhiyuan Liu · 2022
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Towards efficient data free black-box adversarial attack
Jie Zhang, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Lei Zhang, and Chao Wu · 2022
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Query-efficient and scalable black-box adversarial attacks on discrete sequential data via bayesian optimization
Deokjae Lee, Seungyong Moon, Junhyeok Lee, and Hyun Oh Song · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Why should adversarial perturbations be imperceptible? rethink the research paradigm in adversarial NLP
Yangyi Chen, Hongcheng Gao, Ganqu Cui, Fanchao Qi, Longtao Huang, Zhiyuan Liu, and Maosong Sun · 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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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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A pathway towards responsible ai generated content
Chen Chen, Jie Fu, and Lingjuan Lyu · 2023
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Adversarial prompting for black box foundation models
Natalie Maus, Patrick Chao, Eric Wong, and Jacob Gardner · 2023
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A pilot study of query-free adversarial attack against stable diffusion
Haomin Zhuang, Yihua Zhang, and Sijia Liu · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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Using punctuation as an adversarial attack on deep learning-based nlp systems: An empirical study
Brian Formento, Chuan-sheng Foo, Anh Tuan Luu, and See Kiong Ng · 2023
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Yangyi Chen, Hongcheng Gao, Ganqu Cui, Lifan Yuan, Dehan Kong, Hanlu Wu, Ning Shi, Bo Yuan, Longtao Huang, Hui Xue, et al · 2023
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