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Small language models (SLMs) have emerged as promising alternatives to large language models (LLMs) due to their low computational demands, enhanced privacy guarantees and comparable performance in specific domains through light-weight…

密码学与安全 · 计算机科学 2025-03-11 Wenhui Zhang , Huiyu Xu , Zhibo Wang , Zeqing He , Ziqi Zhu , Kui Ren

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…

密码学与安全 · 计算机科学 2026-01-01 Yuan Xin , Dingfan Chen , Linyi Yang , Michael Backes , Xiao Zhang

In recent years, Large Language Models (LLMs) have garnered considerable attention for their remarkable abilities in natural language processing tasks. However, their widespread adoption has raised concerns pertaining to trust and safety.…

人工智能 · 计算机科学 2025-07-01 Doohee You , Dan Chon

Robust verbal confidence generated by large language models (LLMs) is crucial for the deployment of LLMs to help ensure transparency, trust, and safety in many applications, including those involving human-AI interactions. In this paper, we…

计算与语言 · 计算机科学 2025-12-19 Stephen Obadinma , Xiaodan Zhu

Large Language Models (LLMs), despite advanced general capabilities, still suffer from numerous safety risks, especially jailbreak attacks that bypass safety protocols. Understanding these vulnerabilities through black-box jailbreak…

密码学与安全 · 计算机科学 2025-05-29 Yao Huang , Yitong Sun , Shouwei Ruan , Yichi Zhang , Yinpeng Dong , Xingxing Wei

Large Language Models (LLMs) are widely applied in decision making, but their deployment is threatened by jailbreak attacks, where adversarial users manipulate model behavior to bypass safety measures. Existing defense mechanisms, such as…

密码学与安全 · 计算机科学 2025-05-30 Yi Wang , Fenghua Weng , Sibei Yang , Zhan Qin , Minlie Huang , Wenjie Wang

The widespread adoption of Large Language Models (LLMs), exemplified by OpenAI's ChatGPT, brings to the forefront the imperative to defend against adversarial threats on these models. These attacks, which manipulate an LLM's output by…

密码学与安全 · 计算机科学 2025-04-04 Amelia Kawasaki , Andrew Davis , Houssam Abbas

Red teaming is critical for identifying vulnerabilities and building trust in current LLMs. However, current automated methods for Large Language Models (LLMs) rely on brittle prompt templates or single-turn attacks, failing to capture the…

机器学习 · 计算机科学 2025-08-07 Roman Belaire , Arunesh Sinha , Pradeep Varakantham

In the rapidly advancing field of artificial intelligence, the concept of Red-Teaming or Jailbreaking large language models (LLMs) has emerged as a crucial area of study. This approach is especially significant in terms of assessing and…

计算与语言 · 计算机科学 2024-05-17 Rima Hazra , Sayan Layek , Somnath Banerjee , Soujanya Poria

Large Language Models (LLMs) have recently emerged as powerful tools in cybersecurity, offering advanced capabilities in malware detection, generation, and real-time monitoring. Numerous studies have explored their application in…

密码学与安全 · 计算机科学 2025-04-11 Hamed Jelodar , Samita Bai , Parisa Hamedi , Hesamodin Mohammadian , Roozbeh Razavi-Far , Ali Ghorbani

With the significant development of large models in recent years, Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a wide range of multimodal understanding and reasoning tasks. Compared to traditional…

计算机视觉与模式识别 · 计算机科学 2024-07-15 Daizong Liu , Mingyu Yang , Xiaoye Qu , Pan Zhou , Yu Cheng , Wei Hu

The advent of Large Language Models (LLMs) has garnered significant popularity and wielded immense power across various domains within Natural Language Processing (NLP). While their capabilities are undeniably impressive, it is crucial to…

机器学习 · 计算机科学 2024-07-31 Sara Abdali , Jia He , CJ Barberan , Richard Anarfi

Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of…

密码学与安全 · 计算机科学 2024-02-28 Gabriel de Jesus Coelho da Silva , Carlos Becker Westphall

Defense in large language models (LLMs) is crucial to counter the numerous attackers exploiting these systems to generate harmful content through manipulated prompts, known as jailbreak attacks. Although many defense strategies have been…

密码学与安全 · 计算机科学 2024-12-11 Bocheng Chen , Hanqing Guo , Qiben Yan

Large Language Models (LLMs) have emerged as a powerful approach for driving offensive penetration-testing tooling. Due to the opaque nature of LLMs, empirical methods are typically used to analyze their efficacy. The quality of this…

密码学与安全 · 计算机科学 2025-06-17 Andreas Happe , Jürgen Cito

The advancement of Large Language Models (LLMs) has significantly impacted various domains, including Web search, healthcare, and software development. However, as these models scale, they become more vulnerable to cybersecurity risks,…

密码学与安全 · 计算机科学 2024-10-01 Qin Liu , Wenjie Mo , Terry Tong , Jiashu Xu , Fei Wang , Chaowei Xiao , Muhao Chen

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

Large Language Models (LLMs) such as ChatGPT and its competitors have caused a revolution in natural language processing, but their capabilities also introduce new security vulnerabilities. This survey provides a comprehensive overview of…

密码学与安全 · 计算机科学 2025-08-26 Miles Q. Li , Benjamin C. M. Fung

Large Language Models (LLMs) have seen rapid adoption in recent years, with industries increasingly relying on them to maintain a competitive advantage. These models excel at interpreting user instructions and generating human-like…

密码学与安全 · 计算机科学 2025-09-09 Andrew Yeo , Daeseon Choi

When building Large Language Models (LLMs), it is paramount to bear safety in mind and protect them with guardrails. Indeed, LLMs should never generate content promoting or normalizing harmful, illegal, or unethical behavior that may…

计算与语言 · 计算机科学 2024-06-25 Simone Tedeschi , Felix Friedrich , Patrick Schramowski , Kristian Kersting , Roberto Navigli , Huu Nguyen , Bo Li