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The advancements in the domain of LLMs in recent years have surprised many, showcasing their remarkable capabilities and diverse applications. Their potential applications in various real-world scenarios have led to significant research on…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Sujith Vemishetty , Advitiya Arora , Anupama Sharma

Graph Neural Networks (GNNs) have demonstrated remarkable performance across various applications, yet they are vulnerable to sophisticated adversarial attacks, particularly node injection attacks. The success of such attacks heavily relies…

Machine Learning · Computer Science 2025-09-17 Jiahao Zhang , Xiaobing Pei , Zhaokun Zhong , Wenqiang Hao , Zhenghao Tang

The rapid development of generative artificial intelligence has made text to video models essential for building future multimodal world simulators. However, these models remain vulnerable to jailbreak attacks, where specially crafted…

Cryptography and Security · Computer Science 2025-04-29 Siyuan Liang , Jiayang Liu , Jiecheng Zhai , Tianmeng Fang , Rongcheng Tu , Aishan Liu , Xiaochun Cao , Dacheng Tao

In recent years, Text-to-Image (T2I) models have garnered significant attention due to their remarkable advancements. However, security concerns have emerged due to their potential to generate inappropriate or Not-Safe-For-Work (NSFW)…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Yihao Huang , Le Liang , Tianlin Li , Xiaojun Jia , Run Wang , Weikai Miao , Geguang Pu , Yang Liu

Text-to-image (T2I) diffusion models have achieved impressive image generation quality and are increasingly fine-tuned for personalized applications. However, these models often inherit unsafe behaviors from toxic pretraining data, raising…

Machine Learning · Computer Science 2025-12-09 Boheng Li , Renjie Gu , Junjie Wang , Leyi Qi , Yiming Li , Run Wang , Zhan Qin , Tianwei Zhang

Text-to-Image (T2I) diffusion models are widely recognized for their ability to generate high-quality and diverse images based on text prompts. However, despite recent advances, these models are still prone to generating unsafe images…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Jiangweizhi Peng , Zhiwei Tang , Gaowen Liu , Charles Fleming , Mingyi Hong

Jailbreak attacks can circumvent model safety guardrails and reveal critical blind spots. Prior attacks on text-to-video (T2V) models typically add adversarial perturbations to obviously unsafe prompts, which are often easy to detect and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zonghao Ying , Moyang Chen , Nizhang Li , Zhiqiang Wang , Wenxin Zhang , Quanchen Zou , Zonglei Jing , Aishan Liu , Xianglong Liu

Existing text-to-image (T2I) diffusion models usually struggle in interpreting complex prompts, especially those with quantity, object-attribute binding, and multi-subject descriptions. In this work, we introduce a semantic panel as the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Yutong Feng , Biao Gong , Di Chen , Yujun Shen , Yu Liu , Jingren Zhou

State-of-the-art Text-to-Image models like Stable Diffusion and DALLE$\cdot$2 are revolutionizing how people generate visual content. At the same time, society has serious concerns about how adversaries can exploit such models to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Yiting Qu , Xinyue Shen , Xinlei He , Michael Backes , Savvas Zannettou , Yang Zhang

Text-to-image (T2I) models, such as Stable Diffusion, have exhibited remarkable performance in generating high-quality images from text descriptions in recent years. However, text-to-image models may be tricked into generating…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Xinfeng Li , Yuchen Yang , Jiangyi Deng , Chen Yan , Yanjiao Chen , Xiaoyu Ji , Wenyuan Xu

Text-to-image (T2I) diffusion models (DMs) have shown promise in generating high-quality images from textual descriptions. The real-world applications of these models require particular attention to their safety and fidelity, but this has…

Cryptography and Security · Computer Science 2023-06-26 Hongcheng Gao , Hao Zhang , Yinpeng Dong , Zhijie Deng

Recent text-to-video (T2V) models can synthesize complex videos from lightweight natural language prompts, raising urgent concerns about safety alignment in the event of misuse in the real world. Prior jailbreak attacks typically rewrite…

Cryptography and Security · Computer Science 2026-03-10 Moyang Chen , Zonghao Ying , Wenzhuo Xu , Quancheng Zou , Deyue Zhang , Dongdong Yang , Xiangzheng Zhang

Text-to-image generative models such as Stable Diffusion and DALL$\cdot$E raise many ethical concerns due to the generation of harmful images such as Not-Safe-for-Work (NSFW) ones. To address these ethical concerns, safety filters are often…

Machine Learning · Computer Science 2023-11-14 Yuchen Yang , Bo Hui , Haolin Yuan , Neil Gong , Yinzhi Cao

While text-to-image diffusion models demonstrate impressive generation capabilities, they also exhibit vulnerability to backdoor attacks, which involve the manipulation of model outputs through malicious triggers. In this paper, for the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Zhongqi Wang , Jie Zhang , Shiguang Shan , Xilin Chen

As text-to-image (T2I) models advance and gain widespread adoption, their associated safety concerns are becoming increasingly critical. Malicious users exploit these models to generate Not-Safe-for-Work (NSFW) images using harmful or…

Cryptography and Security · Computer Science 2025-12-10 Yiming Wang , Jiahao Chen , Qingming Li , Tong Zhang , Rui Zeng , Xing Yang , Shouling Ji

Despite their superb capabilities, Vision-Language Models (VLMs) have been shown to be vulnerable to jailbreak attacks. While recent jailbreaks have achieved notable progress, their effectiveness and efficiency can still be improved. In…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Yunhan Zhao , Xiang Zheng , Xingjun Ma

Jailbreak attacks on multimodal AI systems remain underexplored, even though unsafe image generation can have more severe consequences than unsafe text and current defenses are relatively immature. We introduce PAST2HARM, a simple yet…

Computation and Language · Computer Science 2026-05-28 Snehasis Mukhopadhyay

Text-based image generation models, such as Stable Diffusion and DALL-E 3, hold significant potential in content creation and publishing workflows, making them the focus in recent years. Despite their remarkable capability to generate…

Computation and Language · Computer Science 2025-06-04 Wenxuan Wang , Kuiyi Gao , Youliang Yuan , Jen-tse Huang , Qiuzhi Liu , Shuai Wang , Wenxiang Jiao , Zhaopeng Tu

Diffusion language models (DLMs) generate tokens in parallel through iterative denoising, which can reduce latency and enable bidirectional conditioning. However, the safety risks posed by jailbreak attacks that exploit this inference…

Artificial Intelligence · Computer Science 2026-02-18 Shojiro Yamabe , Jun Sakuma

Text-to-Image (T2I) generation is a popular AI-generated content (AIGC) technology enabling diverse and creative image synthesis. However, some outputs may contain Not Safe For Work (NSFW) content (e.g., violence), violating community…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mingrui Liu , Sixiao Zhang , Cheng Long