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With the advancement of technology, large language models (LLMs) have achieved remarkable performance across various natural language processing (NLP) tasks, powering LLM-integrated applications like Microsoft Copilot. However, as LLMs…

Cryptography and Security · Computer Science 2025-08-05 Yulin Chen , Haoran Li , Zihao Zheng , Yangqiu Song , Dekai Wu , Bryan Hooi

Recent successes suggest that an image can be manipulated by a text prompt, e.g., a landscape scene on a sunny day is manipulated into the same scene on a rainy day driven by a text input "raining". These approaches often utilize a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Seung Hyun Lee , Gyeongrok Oh , Wonmin Byeon , Sang Ho Yoon , Jinkyu Kim , Sangpil Kim

Large language models (LLMs) have shown remarkable performance across a range of NLP tasks. However, their strong instruction-following capabilities and inability to distinguish instructions from data content make them vulnerable to…

Cryptography and Security · Computer Science 2025-10-07 Yulin Chen , Haoran Li , Yuexin Li , Yue Liu , Yangqiu Song , Bryan Hooi

Ultrasound is widely used in clinical practice due to its portability, cost-effectiveness, safety, and real-time imaging capabilities. However, image acquisition and interpretation remain highly operator dependent, motivating the…

Large vision-language models (LVLMs) have emerged as a powerful paradigm for multimodal intelligence, but their growing deployment also expands the attack surface of prompt injection. Despite this growing concern, existing attacks still…

Cryptography and Security · Computer Science 2026-05-18 Hao Yang , Zhuo Ma , Yang Liu , Yilong Yang , Guancheng Wang , JianFeng Ma

The rise of multimodal large language models has introduced innovative human-machine interaction paradigms but also significant challenges in machine learning safety. Audio-Language Models (ALMs) are especially relevant due to the intuitive…

Machine Learning · Computer Science 2025-07-11 Isha Gupta , David Khachaturov , Robert Mullins

Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to different prompt-based attacks, generating harmful content or sensitive information. Both closed-source and open-source LLMs are underinvestigated for these…

Cryptography and Security · Computer Science 2025-05-21 Jiawen Wang , Pritha Gupta , Ivan Habernal , Eyke Hüllermeier

Large Language Models (LLMs) excel in processing and generating human language, powered by their ability to interpret and follow instructions. However, their capabilities can be exploited through prompt injection attacks. These attacks…

Artificial Intelligence · Computer Science 2024-03-11 Xiaogeng Liu , Zhiyuan Yu , Yizhe Zhang , Ning Zhang , Chaowei Xiao

Recently, Large language models (LLMs) with powerful general capabilities have been increasingly integrated into various Web applications, while undergoing alignment training to ensure that the generated content aligns with user intent and…

Computation and Language · Computer Science 2023-10-17 Shuyu Jiang , Xingshu Chen , Rui Tang

The recent success of the generative model shows that leveraging the multi-modal embedding space can manipulate an image using text information. However, manipulating an image with other sources rather than text, such as sound, is not easy…

Graphics · Computer Science 2021-12-02 Seung Hyun Lee , Wonseok Roh , Wonmin Byeon , Sang Ho Yoon , Chan Young Kim , Jinkyu Kim , Sangpil Kim

The integration of Large Language Models (LLMs) like GPT-4o into robotic systems represents a significant advancement in embodied artificial intelligence. These models can process multi-modal prompts, enabling them to generate more…

Robotics · Computer Science 2024-09-10 Wenxiao Zhang , Xiangrui Kong , Conan Dewitt , Thomas Braunl , Jin B. Hong

Jailbreak attacks to Large audio-language models (LALMs) are studied recently, but they exclusively focused on the attack scenario where the adversary can fully manipulate user prompts (named strong adversary) and limited in effectiveness,…

Cryptography and Security · Computer Science 2026-02-04 Guangke Chen , Fu Song , Zhe Zhao , Xiaojun Jia , Yang Liu , Yanchen Qiao , Weizhe Zhang , Weiping Tu , Yuhong Yang , Bo Du

The emergence of multimodal large language models has redefined the agent paradigm by integrating language and vision modalities with external data sources, enabling agents to better interpret human instructions and execute increasingly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Le Wang , Zonghao Ying , Tianyuan Zhang , Siyuan Liang , Shengshan Hu , Mingchuan Zhang , Aishan Liu , Xianglong Liu

With the rapid advancement of multimodal learning, pre-trained Vision-Language Models (VLMs) such as CLIP have demonstrated remarkable capacities in bridging the gap between visual and language modalities. However, these models remain…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Jiaming Zhang , Xingjun Ma , Xin Wang , Lingyu Qiu , Jiaqi Wang , Yu-Gang Jiang , Jitao Sang

Prompt injection attacks manipulate large language models (LLMs) by misleading them to deviate from the original input instructions and execute maliciously injected instructions, because of their instruction-following capabilities and…

Cryptography and Security · Computer Science 2025-10-07 Yulin Chen , Haoran Li , Yuan Sui , Yufei He , Yue Liu , Yangqiu Song , Bryan Hooi

Large Language Models (LLMs) have demonstrated exceptional proficiency in instruction-following, becoming increasingly crucial across various applications. However, this capability brings with it the risk of prompt injection attacks, where…

Computation and Language · Computer Science 2023-11-28 Zekun Li , Baolin Peng , Pengcheng He , Xifeng Yan

Large language models (LLMs) have transformed the development of embodied intelligence. By providing a few contextual demonstrations, developers can utilize the extensive internal knowledge of LLMs to effortlessly translate complex tasks…

Artificial Intelligence · Computer Science 2024-08-07 Aishan Liu , Yuguang Zhou , Xianglong Liu , Tianyuan Zhang , Siyuan Liang , Jiakai Wang , Yanjun Pu , Tianlin Li , Junqi Zhang , Wenbo Zhou , Qing Guo , Dacheng Tao

Large Language Models (LLMs), including GPT-3.5, LLaMA, and PaLM, seem to be knowledgeable and able to adapt to many tasks. However, we still cannot completely trust their answers, since LLMs suffer from \textbf{hallucination}\textemdash…

Computation and Language · Computer Science 2024-08-06 Jia-Yu Yao , Kun-Peng Ning , Zhen-Hui Liu , Mu-Nan Ning , Yu-Yang Liu , Li Yuan

Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work (NSFW) content via jailbreak attacks. Existing jailbreak…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Xingkai Peng , Jun Jiang , Meng Tong , Shuai Li , Weiming Zhang , Nenghai Yu , Kejiang Chen

Multimodal large language models (MLLMs) equip pre-trained large-language models (LLMs) with visual capabilities. While textual prompting in LLMs has been widely studied, visual prompting has emerged for more fine-grained and free-form…