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Text-to-motion (T2M) generation with diffusion backbones achieves strong realism and alignment. Safety concerns in T2M methods have been raised in recent years; existing methods replace discrete VQ-VAE codebook entries to steer the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Yiling Wang , Zeyu Zhang , Yiran Wang , Hao Tang

As large language models (LLMs) are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model alignment to trigger harmful outputs, present significant risks, with existing studies…

Cryptography and Security · Computer Science 2026-01-01 Yuan Xin , Dingfan Chen , Linyi Yang , Michael Backes , Xiao Zhang

The rapid advancement of text-to-image (T2I) models, such as Stable Diffusion, has enhanced their capability to synthesize images from textual prompts. However, this progress also raises significant risks of misuse, including the generation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Yu Xie , Chengjie Zeng , Lingyun Zhang , Yanwei Fu

Jailbreak attacks represent one of the most sophisticated threats to the security of large language models (LLMs). To deal with such risks, we introduce an innovative framework that can help evaluate the effectiveness of jailbreak attacks…

Computation and Language · Computer Science 2025-03-19 Dong Shu , Chong Zhang , Mingyu Jin , Zihao Zhou , Lingyao Li , Yongfeng Zhang

Jailbreak prompts are a practical and evolving threat to large language models (LLMs), particularly in agentic systems that execute tools over untrusted content. Many attacks exploit long-context hiding, semantic camouflage, and lightweight…

Cryptography and Security · Computer Science 2026-02-19 Doron Shavit

Text-to-Image (T2I) models have gained widespread adoption across various applications. Despite the success, the potential misuse of T2I models poses significant risks of generating Not-Safe-For-Work (NSFW) content. To investigate the…

Cryptography and Security · Computer Science 2025-08-07 Xinqi Lyu , Yihao Liu , Yanjie Li , Bin Xiao

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

Image-to-Video (I2V) generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the security of such multimodal systems, particularly their vulnerability to jailbreak attacks,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Songping Wang , Rufan Qian , Yueming Lyu , Qinglong Liu , Linzhuang Zou , Jie Qin , Songhua Liu , Caifeng Shan

Large language models have become increasingly prominent, also signaling a shift towards multimodality as the next frontier in artificial intelligence, where their embeddings are harnessed as prompts to generate textual content.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Jiachen Sun , Changsheng Wang , Jiongxiao Wang , Yiwei Zhang , Chaowei Xiao

Large Language Models (LLMs) have transformed task automation and content generation across various domains while incorporating safety filters to prevent misuse. We introduce a novel jailbreaking framework that employs distributed prompt…

Cryptography and Security · Computer Science 2025-04-01 Johan Wahréus , Ahmed Hussain , Panos Papadimitratos

Text-to-image (T2I) models such as Stable Diffusion and DALLE remain susceptible to generating harmful or Not-Safe-For-Work (NSFW) content under jailbreak attacks despite deployed safety filters. Existing jailbreak attacks either rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Haolun Zheng , Yu He , Tailun Chen , Shuo Shao , Zhixuan Chu , Hongbin Zhou , Lan Tao , Zhan Qin , Kui Ren

Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text prompts raises security concerns if exploited maliciously.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Honglei Miao , Fan Ma , Ruijie Quan , Kun Zhan , Yi Yang

Text-to-Image(T2I) models have achieved remarkable success in image generation and editing, yet these models still have many potential issues, particularly in generating inappropriate or Not-Safe-For-Work(NSFW) content. Strengthening…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Sensen Gao , Xiaojun Jia , Yihao Huang , Ranjie Duan , Jindong Gu , Yang Bai , Yang Liu , Qing Guo

Multimodal large language models (MLLMs) excel in vision-language tasks but also pose significant risks of generating harmful content, particularly through jailbreak attacks. Jailbreak attacks refer to intentional manipulations that bypass…

Cryptography and Security · Computer Science 2025-07-18 Yi Nian , Shenzhe Zhu , Yuehan Qin , Li Li , Ziyi Wang , Chaowei Xiao , Yue Zhao

Large language models (LLMs) often fail to reason under temporal cutoffs: when prompted to answer from the standpoint of an earlier time, they exploit knowledge that became available only later. We study this failure through the lens of…

Artificial Intelligence · Computer Science 2026-05-15 Chenlu Ding , Jiancan Wu , Yanchen Luo , Zheyuan Liu , Yancheng Yuan , Xiang Wang

Jailbreaking in Large Language Models (LLMs) threatens their safe use in sensitive domains like education by allowing users to bypass ethical safeguards. This study focuses on detecting jailbreaks in 2-Sigma, a clinical education platform…

Large language models (LLMs) have demonstrated remarkable capabilities, yet they also introduce novel security challenges. For instance, prompt jailbreaking attacks involve adversaries crafting sophisticated prompts to elicit responses from…

Artificial Intelligence · Computer Science 2025-09-30 Zhaoqi Wang , Daqing He , Zijian Zhang , Xin Li , Liehuang Zhu , Meng Li , Jiamou Liu

Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

Large Language Models (LLMs) have been equipped with safety mechanisms to prevent harmful outputs, but these guardrails can often be bypassed through "jailbreak" prompts. This paper introduces a novel graph-based approach to systematically…

Cryptography and Security · Computer Science 2025-04-18 Sinan He , An Wang

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
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