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The rapid proliferation of multimodal generative models has sparked critical discussions on their reliability, fairness and potential for misuse. While text-to-image models excel at producing high-fidelity, user-guided content, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jordan Vice , Naveed Akhtar , Leonid Sigal , Richard Hartley , Ajmal Mian

We present a novel task and benchmark for evaluating the ability of text-to-image(T2I) generation models to produce images that align with commonsense in real life, which we call Commonsense-T2I. Given two adversarial text prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Xingyu Fu , Muyu He , Yujie Lu , William Yang Wang , Dan Roth

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

Robustness is essential for deep neural networks, especially in security-sensitive applications. To this end, randomized smoothing provides theoretical guarantees for certifying robustness against adversarial perturbations. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Jiachen Lei , Julius Berner , Jiongxiao Wang , Zhongzhu Chen , Zhongjia Ba , Kui Ren , Jun Zhu , Anima Anandkumar

Text-to-image generation (T2I) refers to the text-guided generation of high-quality images. In the past few years, T2I has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review 141 works…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Pengfei Yang , Ngai-Man Cheung , Xinda Ma

Crafting adversarial examples has become an important technique to evaluate the robustness of deep neural networks (DNNs). However, most existing works focus on attacking the image classification problem since its input space is continuous…

Machine Learning · Computer Science 2020-04-22 Minhao Cheng , Jinfeng Yi , Pin-Yu Chen , Huan Zhang , Cho-Jui Hsieh

Recent works show that text-to-image generative models are surprisingly vulnerable to a variety of poisoning attacks. Empirical results find that these models can be corrupted by altering associations between individual text prompts and…

Cryptography and Security · Computer Science 2024-09-20 Wenxin Ding , Cathy Y. Li , Shawn Shan , Ben Y. Zhao , Haitao Zheng

Text-to-Image(T2I) models typically deploy safety filters to prevent the generation of sensitive images. Unfortunately, recent jailbreaking attack methods manually design instructions for the LLM to generate adversarial prompts, which…

Cryptography and Security · Computer Science 2025-11-24 Chenyu Zhang , Lanjun Wang , Yiwen Ma , Wenhui Li , An-An Liu

Recent text-to-image (T2I) models have exhibited remarkable performance in generating high-quality images from text descriptions. However, these models are vulnerable to misuse, particularly generating not-safe-for-work (NSFW) content, such…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Lingzhi Yuan , Xinfeng Li , Chejian Xu , Guanhong Tao , Xiaojun Jia , Yihao Huang , Wei Dong , Yang Liu , Bo Li

This paper introduces the first gradient-based framework for prompt optimization in text-to-image diffusion models. We formulate prompt engineering as a discrete optimization problem over the language space. Two major challenges arise in…

Machine Learning · Computer Science 2024-07-03 Ruochen Wang , Ting Liu , Cho-Jui Hsieh , Boqing Gong

Aligning Text-to-Image (T2I) generation models with human preferences increasingly relies on image reward models that score or rank generated images according to prompt alignment and perceptual quality. Existing reward models are commonly…

Artificial Intelligence · Computer Science 2026-05-22 Kuei-Chun Kao , Daixuan Huo , Yuanhao Ban , Cho-Jui Hsieh

Text-to-image (T2I) models have gained significant popularity. Most of these are diffusion models with unique computational characteristics, distinct from both traditional small-scale ML models and large language models. They are highly…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Shubham Agarwal , Subrata Mitra , Saud Iqbal

The recent advances in diffusion models (DMs) have revolutionized the generation of realistic and complex images. However, these models also introduce potential safety hazards, such as producing harmful content and infringing data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Yimeng Zhang , Jinghan Jia , Xin Chen , Aochuan Chen , Yihua Zhang , Jiancheng Liu , Ke Ding , Sijia Liu

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

Image attribution -- matching an image back to a trusted source -- is an emerging tool in the fight against online misinformation. Deep visual fingerprinting models have recently been explored for this purpose. However, they are not robust…

Computer Vision and Pattern Recognition · Computer Science 2022-02-28 Maksym Andriushchenko , Xiaoyang Rebecca Li , Geoffrey Oxholm , Thomas Gittings , Tu Bui , Nicolas Flammarion , John Collomosse

Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity. These advancements have sparked research in fake image detection and attribution, yet prior studies have not fully explored the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Katherine Xu , Lingzhi Zhang , Jianbo Shi

Probabilistic model checking is a useful technique for specifying and verifying properties of stochastic systems including randomized protocols and reinforcement learning models. Existing methods rely on the assumed structure and…

Cryptography and Security · Computer Science 2022-08-02 Lisa Oakley , Alina Oprea , Stavros Tripakis

Text-to-image (T2I) models have significantly advanced in producing high-quality images. However, such models have the ability to generate images containing not-safe-for-work (NSFW) content, such as pornography, violence, political content,…

Cryptography and Security · Computer Science 2025-05-15 Longtian Wang , Xiaofei Xie , Tianlin Li , Yuhan Zhi , Chao Shen

The Stable Diffusion Model (SDM) is a popular and efficient text-to-image (t2i) generation and image-to-image (i2i) generation model. Although there have been some attempts to reduce sampling steps, model distillation, and network…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Jinchao Zhu , Yuxuan Wang , Xiaobing Tu , Siyuan Pan , Pengfei Wan , Gao Huang

We study the design of computationally efficient algorithms with provable guarantees, that are robust to adversarial (test time) perturbations. While there has been an proliferation of recent work on this topic due to its connections to…

Machine Learning · Computer Science 2019-11-13 Pranjal Awasthi , Abhratanu Dutta , Aravindan Vijayaraghavan
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