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Integrated Speech and Large Language Models (SLMs) that can follow speech instructions and generate relevant text responses have gained popularity lately. However, the safety and robustness of these models remains largely unclear. In this…

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…

计算与语言 · 计算机科学 2025-07-25 Xuandong Zhao , Xianjun Yang , Tianyu Pang , Chao Du , Lei Li , Yu-Xiang Wang , William Yang Wang

"Jailbreak" is a major safety concern of Large Language Models (LLMs), which occurs when malicious prompts lead LLMs to produce harmful outputs, raising issues about the reliability and safety of LLMs. Therefore, an effective evaluation of…

计算与语言 · 计算机科学 2025-02-04 Lingrui Mei , Shenghua Liu , Yiwei Wang , Baolong Bi , Jiayi Mao , Xueqi Cheng

Large language models (LLMs) have achieved impressive performance across natural language tasks and are increasingly deployed in real-world applications. Despite extensive safety alignment efforts, recent studies show that such alignment is…

人工智能 · 计算机科学 2026-02-02 Yinzhi Zhao , Ming Wang , Shi Feng , Xiaocui Yang , Daling Wang , Yifei Zhang

The adoption of large language models (LLMs) in many applications, from customer service chat bots and software development assistants to more capable agentic systems necessitates research into how to secure these systems. Attacks like…

密码学与安全 · 计算机科学 2024-12-03 Erick Galinkin , Martin Sablotny

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 emerged as powerful re-rankers. Recent research has however showed that simple prompt injections embedded within a candidate document (i.e., jailbreak prompt attacks) can significantly alter an LLM's…

密码学与安全 · 计算机科学 2026-02-20 Yu Yin , Shuai Wang , Bevan Koopman , Guido Zuccon

Large Language Models (LLMs), used in creative writing, code generation, and translation, generate text based on input sequences but are vulnerable to jailbreak attacks, where crafted prompts induce harmful outputs. Most jailbreak prompt…

计算与语言 · 计算机科学 2024-02-28 Xiaoxia Li , Siyuan Liang , Jiyi Zhang , Han Fang , Aishan Liu , Ee-Chien Chang

Large Language Models (LLMs) demonstrate outstanding performance in their reservoir of knowledge and understanding capabilities, but they have also been shown to be prone to illegal or unethical reactions when subjected to jailbreak…

While safety-aligned large language models (LLMs) are increasingly used as the cornerstone for powerful systems such as multi-agent frameworks to solve complex real-world problems, they still suffer from potential adversarial queries, such…

密码学与安全 · 计算机科学 2025-01-03 Miao Yu , Junfeng Fang , Yingjie Zhou , Xing Fan , Kun Wang , Shirui Pan , Qingsong Wen

Jailbreaking techniques trick Large Language Models (LLMs) into producing restricted output, posing a potential threat. One line of defense is to use another LLM as a Judge to evaluate the harmfulness of generated text. However, we reveal…

计算与语言 · 计算机科学 2025-08-19 Zhipeng Wei , Yuqi Liu , N. Benjamin Erichson

Large language models (LLMs) are widely applied in various fields of society due to their powerful reasoning, understanding, and generation capabilities. However, the security issues associated with these models are becoming increasingly…

计算与语言 · 计算机科学 2025-05-30 Yanxu Mao , Peipei Liu , Tiehan Cui , Zhaoteng Yan , Congying Liu , Datao You

Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs). This paper delves into the mechanisms behind such successful…

计算与语言 · 计算机科学 2024-02-27 Huijie Lv , Xiao Wang , Yuansen Zhang , Caishuang Huang , Shihan Dou , Junjie Ye , Tao Gui , Qi Zhang , Xuanjing Huang

Recently, Multimodal Large Language Models (MLLMs) have demonstrated their superior ability in understanding multimodal content. However, they remain vulnerable to jailbreak attacks, which exploit weaknesses in their safety alignment to…

密码学与安全 · 计算机科学 2025-08-29 Wenzhuo Xu , Zhipeng Wei , Xiongtao Sun , Zonghao Ying , Deyue Zhang , Dongdong Yang , Xiangzheng Zhang , Quanchen Zou

Jailbreak attacks pose a serious threat to the safety of Large Language Models (LLMs) by crafting adversarial prompts that bypass alignment mechanisms, causing the models to produce harmful, restricted, or biased content. In this paper, we…

机器学习 · 计算机科学 2025-08-22 Xiangman Li , Xiaodong Wu , Qi Li , Jianbing Ni , Rongxing Lu

We find that language models have difficulties generating fallacious and deceptive reasoning. When asked to generate deceptive outputs, language models tend to leak honest counterparts but believe them to be false. Exploiting this…

计算与语言 · 计算机科学 2025-05-26 Yue Zhou , Henry Peng Zou , Barbara Di Eugenio , Yang Zhang

The recent surge in jailbreaking attacks has revealed significant vulnerabilities in Large Language Models (LLMs) when exposed to malicious inputs. While various defense strategies have been proposed to mitigate these threats, there has…

计算与语言 · 计算机科学 2025-02-24 Tianlong Li , Zhenghua Wang , Wenhao Liu , Muling Wu , Shihan Dou , Changze Lv , Xiaohua Wang , Xiaoqing Zheng , Xuanjing Huang

The rapid progress of large language models (LLMs) is shifting semantic search toward a question-answering paradigm, where users ask questions and LLMs generate responses. In high-stake domains such as law, retrieval-augmented generation…

计算与语言 · 计算机科学 2026-05-25 Souvick Das , Sallam Abualhaija , Domenico Bianculli

The recent breakthrough in large language models (LLMs) such as ChatGPT has revolutionized production processes at an unprecedented pace. Alongside this progress also comes mounting concerns about LLMs' susceptibility to jailbreaking…

机器学习 · 计算机科学 2024-05-24 Tianrong Zhang , Bochuan Cao , Yuanpu Cao , Lu Lin , Prasenjit Mitra , Jinghui Chen

Despite extensive alignment efforts, Large Vision-Language Models (LVLMs) remain vulnerable to jailbreak attacks, posing serious safety risks. To address this, existing detection methods either learn attack-specific parameters, which…

计算机视觉与模式识别 · 计算机科学 2025-10-21 Shuang Liang , Zhihao Xu , Jialing Tao , Hui Xue , Xiting Wang