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Large Language Model (LLM) is changing the software development paradigm and has gained huge attention from both academia and industry. Researchers and developers collaboratively explore how to leverage the powerful problem-solving ability…

密码学与安全 · 计算机科学 2024-11-05 Qiang Hu , Xiaofei Xie , Sen Chen , Lei Ma

Recent researches have shown that Large Language Models (LLMs) are susceptible to a security threat known as Backdoor Attack. The backdoored model will behave well in normal cases but exhibit malicious behaviours on inputs inserted with a…

密码学与安全 · 计算机科学 2024-04-04 Yunzhuo Hao , Wenkai Yang , Yankai Lin

Large language models (LLMs) have demonstrated remarkable capabilities, but their power comes with significant security considerations. While extensive research has been conducted on the safety of LLMs in chat mode, the security…

密码学与安全 · 计算机科学 2024-12-25 Zihui Wu , Haichang Gao , Jianping He , Ping Wang

Large Language Models (LLMs) are increasingly applied in high-stakes domains such as finance, healthcare, and education, where reliable multi-turn interactions with users are essential. However, existing work on confidence estimation and…

计算与语言 · 计算机科学 2026-04-08 Zhaohan Zhang , Chengzhengxu Li , Xiaoming Liu , Chao Shen , Ziquan Liu , Ioannis Patras

Online abuse has grown increasingly complex, spanning toxic language, harassment, manipulation, and fraudulent behavior. Traditional machine-learning approaches dependent on static classifiers and labor-intensive labeling struggle to keep…

计算与语言 · 计算机科学 2026-04-02 Suraj Kath , Sanket Badhe , Preet Shah , Ashwin Sampathkumar , Shivani Gupta

With the rapid advancement of artificial intelligence, Large Language Models (LLMs) have shown remarkable capabilities in Natural Language Processing (NLP), including content generation, human-computer interaction, machine translation, and…

计算与语言 · 计算机科学 2025-10-31 Songyang Liu , Chaozhuo Li , Jiameng Qiu , Xi Zhang , Feiran Huang , Litian Zhang , Yiming Hei , Philip S. Yu

Large Language Model (LLM) alignment aims to ensure that LLM outputs match with human values. Researchers have demonstrated the severity of alignment problems with a large spectrum of jailbreak techniques that can induce LLMs to produce…

计算与语言 · 计算机科学 2024-02-06 Xiaolong Jin , Zhuo Zhang , Xiangyu Zhang

Large Language Models (LLMs) rapidly reshape modern life, advancing fields from healthcare to education and beyond. However, alongside their remarkable capabilities lies a significant threat: the susceptibility of these models to…

计算与语言 · 计算机科学 2025-05-16 Michael Fire , Yitzhak Elbazis , Adi Wasenstein , Lior Rokach

Large Language Models (LLMs) are increasingly used to control robotic systems such as drones, but their risks of causing physical threats and harm in real-world applications remain unexplored. Our study addresses the critical gap in…

机器学习 · 计算机科学 2026-02-20 Yung-Chen Tang , Pin-Yu Chen , Tsung-Yi Ho

Most traditional AI safety research has approached AI models as machines and centered on algorithm-focused attacks developed by security experts. As large language models (LLMs) become increasingly common and competent, non-expert users can…

计算与语言 · 计算机科学 2024-01-25 Yi Zeng , Hongpeng Lin , Jingwen Zhang , Diyi Yang , Ruoxi Jia , Weiyan Shi

As large language models (LLMs) become easily accessible nowadays, the trade-off between safety and helpfulness can significantly impact user experience. A model that prioritizes safety will cause users to feel less engaged and assisted…

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) are intensively used to assist security analysts in counteracting the rapid exploitation of cyber threats, wherein LLMs offer cyber threat intelligence (CTI) to support vulnerability assessment and incident…

密码学与安全 · 计算机科学 2025-10-03 Luoxi Tang , Yuqiao Meng , Ankita Patra , Weicheng Ma , Muchao Ye , Zhaohan Xi

The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications. However, the risks associated with using LLMs in medical applications have not been…

Evaluating aligned large language models' (LLMs) ability to recognize and reject unsafe user requests is crucial for safe, policy-compliant deployments. Existing evaluation efforts, however, face three limitations that we address with…

Large language models (LLMs) have made significant strides, extending their applications to dialogue systems, automated content creation, and domain-specific advisory tasks. However, as their use grows, concerns have emerged regarding their…

人工智能 · 计算机科学 2025-07-01 Bing Song , Jianing Liu , Sisi Jian , Chenyang Wu , Vinayak Dixit

Large language models (LLMs) represent significant breakthroughs in artificial intelligence and hold potential for applications within smart grids. However, as demonstrated in previous literature, AI technologies are susceptible to various…

密码学与安全 · 计算机科学 2025-04-22 Jiangnan Li , Yingyuan Yang , Jinyuan Sun

The evolution of Generative AI and the capabilities of the newly released Large Language Models (LLMs) open new opportunities in software engineering. However, they also lead to new challenges in cybersecurity. Recently, researchers have…

密码学与安全 · 计算机科学 2023-09-08 Mika Beckerich , Laura Plein , Sergio Coronado

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks in various domains. Despite their impressive performance, they can be unreliable due to factual errors in their generations. Assessing their…

计算与语言 · 计算机科学 2024-03-26 Jiahui Geng , Fengyu Cai , Yuxia Wang , Heinz Koeppl , Preslav Nakov , Iryna Gurevych

Social media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection. In this work, we bring the arms race to the next level by investigating the…

计算与语言 · 计算机科学 2024-07-08 Shangbin Feng , Herun Wan , Ningnan Wang , Zhaoxuan Tan , Minnan Luo , Yulia Tsvetkov