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Recently, various types of Text-to-Image (T2I) models have emerged (such as DALL-E and Stable Diffusion), and showing their advantages in different aspects. Therefore, some third-party service platforms collect different model interfaces…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Ji Guo , Wenbo Jiang , Rui Zhang , Guoming Lu , Hongwei Li

The proliferation of Large Language Models (LLMs) has introduced critical security challenges, where adversarial actors can manipulate input prompts to cause significant harm and circumvent safety alignments. These prompt-based attacks…

Jailbreaking large language models (LLMs) has emerged as a critical security challenge with the widespread deployment of conversational AI systems. Adversarial users exploit these models through carefully crafted prompts to elicit…

Cryptography and Security · Computer Science 2026-02-23 Sri Durga Sai Sowmya Kadali , Evangelos E. Papalexakis

Video Large Language Models (VLMs) have achieved strong performance on various vision-language tasks, yet their practical use is limited by the massive number of visual tokens produced from raw video frames, which quickly exhausts the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Guangyu Sun , Archit Singhal , Burak Uzkent , Mubarak Shah , Chen Chen , Garin Kessler

Large language models (LLMs) are vulnerable to jailbreak attacks - resulting in harmful, unethical, or biased text generations. However, existing jailbreaking methods are computationally costly. In this paper, we propose the weak-to-strong…

Computation and Language · Computer Science 2025-07-25 Xuandong Zhao , Xianjun Yang , Tianyu Pang , Chao Du , Lei Li , Yu-Xiang Wang , William Yang Wang

Using risky text prompts, such as pornography and violent prompts, to test the safety of text-to-image (T2I) models is a critical task. However, existing risky prompt datasets are limited in three key areas: 1) limited risky categories, 2)…

Cryptography and Security · Computer Science 2025-11-24 Chenyu Zhang , Tairen Zhang , Lanjun Wang , Ruidong Chen , Wenhui Li , Anan Liu

Vision-language models (VLMs) extend large language models (LLMs) with vision encoders, enabling text generation conditioned on both images and text. However, this multimodal integration expands the attack surface by exposing the model to…

Machine Learning · Computer Science 2026-02-03 Kaiyuan Cui , Yige Li , Yutao Wu , Xingjun Ma , Sarah Erfani , Christopher Leckie , Hanxun Huang

Generating high-quality videos from complex temporal descriptions that contain multiple sequential actions is a key unsolved problem. Existing methods are constrained by an inherent trade-off: using multiple short prompts fed sequentially…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Hongyu Zhang , Yufan Deng , Zilin Pan , Peng-Tao Jiang , Bo Li , Qibin Hou , Zhiyang Dou , Zhen Dong , Daquan Zhou

Recent video generation models have revealed the emergence of Chain-of-Frame (CoF) reasoning, enabling frame-by-frame visual inference. With this capability, video models have been successfully applied to various visual tasks (e.g., maze…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Chengzhuo Tong , Mingkun Chang , Shenglong Zhang , Yuran Wang , Cheng Liang , Zhizheng Zhao , Ruichuan An , Bohan Zeng , Yang Shi , Yifan Dai , Ziming Zhao , Guanbin Li , Pengfei Wan , Yuanxing Zhang , Wentao Zhang

Recent advancements in text-to-image (T2I) generation using diffusion models have enabled cost-effective video-editing applications by leveraging pre-trained models, eliminating the need for resource-intensive training. However, the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Yangfan He , Sida Li , Jianhui Wang , Kun Li , Xinyuan Song , Xinhang Yuan , Keqin Li , Kuan Lu , Menghao Huo , Jingqun Tang , Yi Xin , Jiaqi Chen , Miao Zhang , Xueqian Wang

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential misuse, particularly in generating inappropriate or…

Cryptography and Security · Computer Science 2024-04-02 Yijun Yang , Ruiyuan Gao , Xiaosen Wang , Tsung-Yi Ho , Nan Xu , Qiang Xu

Multimodal Large Language Models (MLLMs) are widely used in various fields due to their powerful cross-modal comprehension and generation capabilities. However, more modalities bring more vulnerabilities to being utilized for jailbreak…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shiji Zhao , Shukun Xiong , Yao Huang , Yan Jin , Zhenyu Wu , Jiyang Guan , Ranjie Duan , Jialing Tao , Hui Xue , Xingxing Wei

Recent advances in text-to-video (T2V) generation with diffusion models have garnered significant attention. However, they typically perform well in scenes with a single object and motion, struggling in compositional scenarios with multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Yuanhang Li , Qi Mao , Lan Chen , Zhen Fang , Lei Tian , Xinyan Xiao , Libiao Jin , Hua Wu

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

Recent advances in text-to-image generative models have raised concerns about their potential to produce harmful content when provided with malicious input text prompts. To address this issue, two main approaches have emerged: (1)…

Machine Learning · Computer Science 2025-11-13 Jiwoo Shin , Byeonghu Na , Mina Kang , Wonhyeok Choi , Il-Chul Moon

In recent years, the rapid development of large language models (LLMs) has achieved remarkable performance across various tasks. However, research indicates that LLMs are vulnerable to jailbreak attacks, where adversaries can induce the…

Cryptography and Security · Computer Science 2024-08-23 Jiawei Zhao , Kejiang Chen , Xiaojian Yuan , Weiming Zhang

Vision-language models bridge visual and linguistic understanding and have proven to be powerful for video recognition tasks. Existing approaches primarily rely on parameter-efficient fine-tuning of image-text pre-trained models, yet they…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Wencheng Zhu , Yuexin Wang , Hongxuan Li , Pengfei Zhu , Qinghua Hu

Text-to-Image (T2I) generation has advanced rapidly in recent years, but they also raise safety concerns due to the potential production of harmful content. In the practical deployments, T2I services typically adopt full-chain defenses that…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Jiangtao Liu , Zhaoxin Wang , Handing Wang , Cong Tian , Yaochu Jin

In this study, we disclose a worrying new vulnerability in Large Language Models (LLMs), which we term \textbf{involuntary jailbreak}. Unlike existing jailbreak attacks, this weakness is distinct in that it does not involve a specific…

Cryptography and Security · Computer Science 2025-12-30 Yangyang Guo , Yangyan Li , Mohan Kankanhalli

Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, which are generally exacerbated by the ambiguity and underspecification of text prompts. In…

Artificial Intelligence · Computer Science 2026-04-21 Chengyi Yang , Pengzhen Li , Jiayin Qi , Aimin Zhou , Ji Wu , Ji Liu
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