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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

The jailbreak attack can bypass the safety measures of a Large Language Model (LLM), generating harmful content. This misuse of LLM has led to negative societal consequences. Currently, there are two main approaches to address jailbreak…

Computation and Language · Computer Science 2024-03-25 Zezhong Wang , Fangkai Yang , Lu Wang , Pu Zhao , Hongru Wang , Liang Chen , Qingwei Lin , Kam-Fai Wong

We explore Multimodal Large Language Models (MLLMs), which integrate LLMs like GPT-4 to handle multimodal data, including text, images, audio, and more. MLLMs demonstrate capabilities such as generating image captions and answering…

Computation and Language · Computer Science 2025-01-09 Shezheng Song , Xiaopeng Li , Shasha Li , Shan Zhao , Jie Yu , Jun Ma , Xiaoguang Mao , Weimin Zhang

By incorporating visual inputs, Multimodal Large Language Models (MLLMs) extend LLMs to support visual reasoning. However, this integration also introduces new vulnerabilities, making MLLMs susceptible to multimodal jailbreak attacks and…

Cryptography and Security · Computer Science 2025-12-04 Beitao Chen , Xinyu Lyu , Lianli Gao , Jingkuan Song , Heng Tao Shen

The robustness and security of large language models (LLMs) has become a prominent research area. One notable vulnerability is the ability to bypass LLM safeguards by translating harmful queries into rare or underrepresented languages, a…

Computation and Language · Computer Science 2025-09-16 Hongliang Li , Jinan Xu , Gengping Cui , Changhao Guan , Fengran Mo , Kaiyu Huang

As large language models (LLMs) become integral to various applications, ensuring both their safety and utility is paramount. Jailbreak attacks, which manipulate LLMs into generating harmful content, pose significant challenges to this…

Cryptography and Security · Computer Science 2025-02-10 Guobin Shen , Dongcheng Zhao , Yiting Dong , Xiang He , Yi Zeng

The aligned Large Language Models (LLMs) are powerful language understanding and decision-making tools that are created through extensive alignment with human feedback. However, these large models remain susceptible to jailbreak attacks,…

Computation and Language · Computer Science 2024-03-22 Xiaogeng Liu , Nan Xu , Muhao Chen , Chaowei Xiao

Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains. However, their potential to generate harmful responses has raised significant societal and regulatory concerns, especially when manipulated by…

Cryptography and Security · Computer Science 2025-06-17 Advait Yadav , Haibo Jin , Man Luo , Jun Zhuang , Haohan Wang

Large Language Models (LLMs) and Vision Language Models (VLMs) have demonstrated impressive capabilities but remain vulnerable to jailbreaking attacks, where adversaries exploit textual or visual triggers to bypass safety guardrails. Recent…

Cryptography and Security · Computer Science 2026-05-15 Yi Wang , Hongye Qiu , Yue Xu , Sibei Yang , Zhan Qin , Minlie Huang , Wenjie Wang

Multimodal Large Language Models (MLLMs) extend the capacity of LLMs to understand multimodal information comprehensively, achieving remarkable performance in many vision-centric tasks. Despite that, recent studies have shown that these…

Computation and Language · Computer Science 2024-10-18 Yue Xu , Xiuyuan Qi , Zhan Qin , Wenjie Wang

Large language models (LLMs) possess strong semantic understanding, driving significant progress in data mining applications. This is further enhanced by large reasoning models (LRMs), which provide explicit multi-step reasoning traces. On…

Machine Learning · Computer Science 2026-04-07 Aobo Chen , Chenxu Zhao , Chenglin Miao , Mengdi Huai

Large language models are aligned to be safe, preventing users from generating harmful content like misinformation or instructions for illegal activities. However, previous work has shown that the alignment process is vulnerable to…

Computation and Language · Computer Science 2024-06-07 Javier Rando , Francesco Croce , Kryštof Mitka , Stepan Shabalin , Maksym Andriushchenko , Nicolas Flammarion , Florian Tramèr

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…

Artificial Intelligence · Computer Science 2025-01-08 Fengxiang Wang , Ranjie Duan , Peng Xiao , Xiaojun Jia , Shiji Zhao , Cheng Wei , YueFeng Chen , Chongwen Wang , Jialing Tao , Hang Su , Jun Zhu , Hui Xue

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…

Cryptography and Security · Computer Science 2024-11-07 Zhao Xu , Fan Liu , Hao Liu

Despite their superior performance on a wide range of domains, large language models (LLMs) remain vulnerable to misuse for generating harmful content, a risk that has been further amplified by various jailbreak attacks. Existing jailbreak…

Cryptography and Security · Computer Science 2025-10-27 Yukun Jiang , Mingjie Li , Michael Backes , Yang Zhang

Alignment in large language models (LLMs) is used to enforce guidelines such as safety. Yet, alignment fails in the face of jailbreak attacks that modify inputs to induce unsafe outputs. In this paper, we introduce and evaluate a new…

Cryptography and Security · Computer Science 2026-02-19 Jean-Charles Noirot Ferrand , Yohan Beugin , Eric Pauley , Ryan Sheatsley , Patrick McDaniel

Multimodal Large Language Models (MLLMs), built upon LLMs, have recently gained attention for their capabilities in image recognition and understanding. However, while MLLMs are vulnerable to adversarial attacks, the transferability of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Chenhe Gu , Jindong Gu , Andong Hua , Yao Qin

The rapid evolution of artificial intelligence (AI) through developments in Large Language Models (LLMs) and Vision-Language Models (VLMs) has brought significant advancements across various technological domains. While these models enhance…

Computation and Language · Computer Science 2025-11-11 Haibo Jin , Leyang Hu , Xinnuo Li , Peiyan Zhang , Chonghan Chen , Jun Zhuang , Haohan Wang

There has been an increasing interest in the alignment of large language models (LLMs) with human values. However, the safety issues of their integration with a vision module, or vision language models (VLMs), remain relatively…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xijia Tao , Shuai Zhong , Lei Li , Qi Liu , Lingpeng Kong

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…

Computation and Language · Computer Science 2024-12-18 Tarun Raheja , Nilay Pochhi , F. D. C. M. Curie
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