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Although large language models (LLMs) demonstrate impressive proficiency in various tasks, they present potential safety risks, such as `jailbreaks', where malicious inputs can coerce LLMs into generating harmful content bypassing safety…

计算与语言 · 计算机科学 2025-11-26 Isack Lee , Haebin Seong

Large language models (LLMs) have opened new opportunities for automated mobile app exploration, an important and challenging problem that used to suffer from the difficulty of generating meaningful UI interactions. However, existing…

软件工程 · 计算机科学 2025-05-19 Shanhui Zhao , Hao Wen , Wenjie Du , Cheng Liang , Yunxin Liu , Xiaozhou Ye , Ye Ouyang , Yuanchun Li

The emerging success of large language models (LLMs) heavily relies on collecting abundant training data from external (untrusted) sources. Despite substantial efforts devoted to data cleaning and curation, well-constructed LLMs have been…

计算与语言 · 计算机科学 2024-02-26 Tianlin Li , Qian Liu , Tianyu Pang , Chao Du , Qing Guo , Yang Liu , Min Lin

Large Language Models (LLMs) have recently demonstrated significant potential in time series forecasting, offering impressive capabilities in handling complex temporal data. However, their robustness and reliability in real-world…

机器学习 · 计算机科学 2025-03-14 Fuqiang Liu , Sicong Jiang , Luis Miranda-Moreno , Seongjin Choi , Lijun Sun

Growing applications of large language models (LLMs) trained by a third party raise serious concerns on the security vulnerability of LLMs.It has been demonstrated that malicious actors can covertly exploit these vulnerabilities in LLMs…

密码学与安全 · 计算机科学 2023-12-11 Shuli Jiang , Swanand Ravindra Kadhe , Yi Zhou , Ling Cai , Nathalie Baracaldo

The open-endedness of large language models (LLMs) combined with their impressive capabilities may lead to new safety issues when being exploited for malicious use. While recent studies primarily focus on probing toxic outputs that can be…

计算与语言 · 计算机科学 2023-11-30 Jiaxin Wen , Pei Ke , Hao Sun , Zhexin Zhang , Chengfei Li , Jinfeng Bai , Minlie Huang

Despite the impressive adaptability of large language models (LLMs), challenges remain in ensuring their security, transparency, and interpretability. Given their susceptibility to adversarial attacks, LLMs need to be defended with an…

人工智能 · 计算机科学 2024-10-11 Tomas Bueno Momcilovic , Beat Buesser , Giulio Zizzo , Mark Purcell , Dian Balta

Recent advancements in large language models (LLMs) have significantly enhanced capabilities in natural language processing and artificial intelligence. These models, including GPT-3.5 and LLaMA-2, have revolutionized text generation,…

计算与语言 · 计算机科学 2024-02-06 Yunhong He , Jianling Qiu , Wei Zhang , Zhengqing Yuan

Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, but their vulnerability to jailbreak attacks poses significant security risks. This survey paper presents a comprehensive analysis…

计算与语言 · 计算机科学 2024-12-18 Tarun Raheja , Nilay Pochhi , F. D. C. M. Curie

Modern life has witnessed the explosion of mobile devices. However, besides the valuable features that bring convenience to end users, security and privacy risks still threaten users of mobile apps. The increasing sophistication of these…

密码学与安全 · 计算机科学 2025-12-02 Tran Thanh Lam Nguyen , Barbara Carminati , Elena Ferrari

Large Language Models (LLMs) have revolutionized content creation across digital platforms, offering unprecedented capabilities in natural language generation and understanding. These models enable beneficial applications such as content…

计算与语言 · 计算机科学 2025-08-14 Chi Zhang , Changjia Zhu , Junjie Xiong , Xiaoran Xu , Lingyao Li , Yao Liu , Zhuo Lu

Although Large Language Models (LLMs) have demonstrated significant capabilities in executing complex tasks in a zero-shot manner, they are susceptible to jailbreak attacks and can be manipulated to produce harmful outputs. Recently, a…

密码学与安全 · 计算机科学 2024-11-07 Zhao Xu , Fan Liu , Hao Liu

Jailbreak attacks aim to exploit large language models (LLMs) by inducing them to generate harmful content, thereby revealing their vulnerabilities. Understanding and addressing these attacks is crucial for advancing the field of LLM…

密码学与安全 · 计算机科学 2026-03-26 Zheng Zhang , Peilin Zhao , Deheng Ye , Hao Wang

As large language models (LLMs) permeate more and more applications, an assessment of their associated security risks becomes increasingly necessary. The potential for exploitation by malicious actors, ranging from disinformation to data…

密码学与安全 · 计算机科学 2024-09-24 Erik Derner , Kristina Batistič , Jan Zahálka , Robert Babuška

Regulatory limits on explicit targeting have not eliminated algorithmic profiling on the Web, as optimisation systems still adapt ad delivery to users' private attributes. The widespread availability of powerful zero-shot multimodal Large…

人机交互 · 计算机科学 2026-01-30 Baiyu Chen , Benjamin Tag , Hao Xue , Daniel Angus , Flora Salim

Small language models (SLMs) have become increasingly prominent in the deployment on edge devices due to their high efficiency and low computational cost. While researchers continue to advance the capabilities of SLMs through innovative…

密码学与安全 · 计算机科学 2025-05-27 Sibo Yi , Tianshuo Cong , Xinlei He , Qi Li , Jiaxing Song

Large Language Models (LLMs) have demonstrated great capabilities in natural language understanding and generation, largely attributed to the intricate alignment process using human feedback. While alignment has become an essential training…

计算与语言 · 计算机科学 2024-09-04 Bocheng Chen , Hanqing Guo , Guangjing Wang , Yuanda Wang , Qiben Yan

Large Language Models (LLMs) are widely deployed in real-world systems. Given their broader applicability, prompt engineering has become an efficient tool for resource-scarce organizations to adopt LLMs for their own purposes. At the same…

密码学与安全 · 计算机科学 2026-02-27 Piyush Jaiswal , Aaditya Pratap , Shreyansh Saraswati , Harsh Kasyap , Somanath Tripathy

This paper focuses on jailbreaking attacks against large language models (LLMs), eliciting them to generate objectionable content in response to harmful user queries. Unlike previous LLM-jailbreak methods that directly orient to LLMs, our…

人工智能 · 计算机科学 2025-12-02 Haoxuan Ji , Zheng Lin , Zhenxing Niu , Xinbo Gao , Gang Hua

Enterprise penetration-testing is often limited by high operational costs and the scarcity of human expertise. This paper investigates the feasibility and effectiveness of using Large Language Model (LLM)-driven autonomous systems to…

密码学与安全 · 计算机科学 2025-09-12 Andreas Happe , Jürgen Cito