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Large language models (LLMs) are popular for high-quality text generation but can produce harmful content, even when aligned with human values through reinforcement learning. Adversarial prompts can bypass their safety measures. We propose…

计算与语言 · 计算机科学 2024-05-03 Mansi Phute , Alec Helbling , Matthew Hull , ShengYun Peng , Sebastian Szyller , Cory Cornelius , Duen Horng Chau

Ensuring the safety and alignment of large language models (LLMs) with human values is crucial for generating responses that are beneficial to humanity. While LLMs have the capability to identify and avoid harmful queries, they remain…

计算与语言 · 计算机科学 2024-10-22 Yihua Zhou , Xiaochuan Shi

Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also why they fail and misbehave is of great societal relevance.…

计算与语言 · 计算机科学 2024-10-16 Julian Coda-Forno , Kristin Witte , Akshay K. Jagadish , Marcel Binz , Zeynep Akata , Eric Schulz

Large Language Models (LLMs) have demonstrated powerful capabilities that render them valuable in different applications, including conversational AI products. It is paramount to ensure the security and reliability of these products by…

计算与语言 · 计算机科学 2025-01-23 Melissa Kazemi Rad , Huy Nghiem , Andy Luo , Sahil Wadhwa , Mohammad Sorower , Stephen Rawls

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

Large Language Models (LLMs) are being enhanced with the ability to use tools and to process multiple modalities. These new capabilities bring new benefits and also new security risks. In this work, we show that an attacker can use visual…

In this study, we propose a homotopy-inspired prompt obfuscation framework to enhance understanding of security and safety vulnerabilities in Large Language Models (LLMs). By systematically applying carefully engineered prompts, we…

密码学与安全 · 计算机科学 2026-01-22 Luis Lazo , Hamed Jelodar , Roozbeh Razavi-Far

While large language models (LLMs) present significant potential for supporting numerous real-world applications and delivering positive social impacts, they still face significant challenges in terms of the inherent risk of privacy…

人工智能 · 计算机科学 2025-01-17 Huandong Wang , Wenjie Fu , Yingzhou Tang , Zhilong Chen , Yuxi Huang , Jinghua Piao , Chen Gao , Fengli Xu , Tao Jiang , Yong Li

The latest advancements in AI and deep learning have led to a breakthrough in large language model (LLM)-based agents such as GPT-4. However, many commercial conversational agent development tools are pipeline-based and have limitations in…

计算与语言 · 计算机科学 2023-09-08 Mina Foosherian , Hendrik Purwins , Purna Rathnayake , Touhidul Alam , Rui Teimao , Klaus-Dieter Thoben

The capacity of large language models (LLMs) to generate honest, harmless, and helpful responses heavily relies on the quality of user prompts. However, these prompts often tend to be brief and vague, thereby significantly limiting the full…

计算与语言 · 计算机科学 2025-07-01 Xiaohua Wang , Zisu Huang , Feiran Zhang , Zhibo Xu , Cenyuan Zhang , Qi Qian , Xiaoqing Zheng , Xuanjing Huang

Large Language Models (LLMs) can generate human-like disinformation, yet their ability to personalise such content across languages and demographics remains underexplored. This study presents the first large-scale, multilingual analysis of…

Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as they integrate more deeply into complex systems, the urgency to scrutinize their security properties grows. This paper surveys research in the…

计算与语言 · 计算机科学 2023-10-18 Erfan Shayegani , Md Abdullah Al Mamun , Yu Fu , Pedram Zaree , Yue Dong , Nael Abu-Ghazaleh

Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these…

计算与语言 · 计算机科学 2024-10-14 Rohan Ajwani , Shashidhar Reddy Javaji , Frank Rudzicz , Zining Zhu

Large Language Models (LLMs) are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote…

密码学与安全 · 计算机科学 2025-09-09 Irdin Pekaric , Philipp Zech , Tom Mattson

Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyzing large amounts of text data, allowing them to perform…

密码学与安全 · 计算机科学 2024-03-15 Biwei Yan , Kun Li , Minghui Xu , Yueyan Dong , Yue Zhang , Zhaochun Ren , Xiuzhen Cheng

The proliferation of large language models (LLMs) has sparked widespread and general interest due to their strong language generation capabilities, offering great potential for both industry and research. While previous research delved into…

人工智能 · 计算机科学 2024-07-09 Lukas Struppek , Minh Hieu Le , Dominik Hintersdorf , Kristian Kersting

While large language models (LLMs) have demonstrated increasing power, they have also given rise to a wide range of harmful behaviors. As representatives, jailbreak attacks can provoke harmful or unethical responses from LLMs, even after…

计算与语言 · 计算机科学 2024-03-01 Nan Xu , Fei Wang , Ben Zhou , Bang Zheng Li , Chaowei Xiao , Muhao Chen

Large Language Models (LLMs) have emerged as powerful tools for automating programming tasks, including security-related ones. However, they can also introduce vulnerabilities during code generation, fail to detect existing vulnerabilities,…

密码学与安全 · 计算机科学 2026-03-18 Enna Basic , Alberto Giaretta

Large Language Models (LLMs) have shown prominent performance in various downstream tasks and prompt engineering plays a pivotal role in optimizing LLMs' performance. This paper, not only as an overview of current prompt engineering…

计算与语言 · 计算机科学 2024-09-18 Haochen Li , Jonathan Leung , Zhiqi Shen

Large Language Models (LLMs) have made significant advances in natural language processing, but their underlying mechanisms are often misunderstood. Despite exhibiting coherent answers and apparent reasoning behaviors, LLMs rely on…

计算与语言 · 计算机科学 2024-08-05 Bo Zhou , Daniel Geißler , Paul Lukowicz