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AI safety training and red-teaming of large language models (LLMs) are measures to mitigate the generation of unsafe content. Our work exposes the inherent cross-lingual vulnerability of these safety mechanisms, resulting from the…

计算与语言 · 计算机科学 2024-01-30 Zheng-Xin Yong , Cristina Menghini , Stephen H. Bach

$ $Large Language Models (LLMs) are being increasingly utilized in various applications, with code generations being a notable example. While previous research has shown that LLMs have the capability to generate both secure and insecure…

Large language models (LLMs) can be used as accessible and intelligent chatbots by constructing natural language queries and directly inputting the prompt into the large language model. However, different prompt' constructions often lead to…

计算与语言 · 计算机科学 2023-12-14 Jinta Weng , Jiarui Zhang , Yue Hu , Daidong Fa , Xiaofeng Xuand , Heyan Huang

Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification.…

计算与语言 · 计算机科学 2024-08-12 Md Nazmus Sakib , Md Athikul Islam , Royal Pathak , Md Mashrur Arifin

Although the integration of large language models (LLMs) into robotics has unlocked transformative capabilities, it has also introduced significant safety concerns, ranging from average-case LLM errors (e.g., hallucinations) to adversarial…

机器人学 · 计算机科学 2026-03-05 Zachary Ravichandran , Alexander Robey , Vijay Kumar , George J. Pappas , Hamed Hassani

As large language models (LLMs) rapidly evolve, they bring significant conveniences to our work and daily lives, but also introduce considerable safety risks. These models can generate texts with social biases or unethical content, and…

计算与语言 · 计算机科学 2024-10-30 Zhihao Liu , Chenhui Hu

The Large Language Models (LLM) are increasingly being deployed in robotics to generate robot control programs for specific user tasks, enabling embodied intelligence. Existing methods primarily focus on LLM training and prompt design that…

机器人学 · 计算机科学 2025-08-27 ZhenDong Chen , ZhanShang Nie , ShiXing Wan , JunYi Li , YongTian Cheng , Shuai Zhao

Large Language Models (LLMs) have become a focal point of research across various domains, including software engineering, where their capabilities are increasingly leveraged. Recent studies have explored the integration of LLMs into…

软件工程 · 计算机科学 2024-10-14 Yi Wen Heng , Zeyang Ma , Zhenhao Li , Dong Jae Kim , Tse-Hsun , Chen

The integration of Large Language Models (LLMs) into robotics has revolutionized their ability to interpret complex human commands and execute sophisticated tasks. However, such paradigm shift introduces critical security vulnerabilities…

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

Cloud systems generate large, heterogeneous log data containing critical infrastructure, application, and security information. Transforming these logs into RDF triples enables their integration into knowledge graphs, improving…

信息检索 · 计算机科学 2026-04-01 Ioana Ramona Martin , Tudor Cioara , Ionut Anghel , Gabriel Arcas

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

High-risk domains pose unique challenges that require language models to provide accurate and safe responses. Despite the great success of large language models (LLMs), such as ChatGPT and its variants, their performance in high-risk…

计算与语言 · 计算机科学 2023-11-28 Chia-Chien Hung , Wiem Ben Rim , Lindsay Frost , Lars Bruckner , Carolin Lawrence

Construction remains one of the most hazardous sectors. Recent advancements in AI, particularly Large Language Models (LLMs), offer promising opportunities for enhancing workplace safety. However, responsible integration of LLMs requires…

人工智能 · 计算机科学 2024-11-14 Farouq Sammour , Jia Xu , Xi Wang , Mo Hu , Zhenyu Zhang

Fine-tuning safety-aligned large language models (LLMs) can substantially compromise their safety. Previous approaches require many safety samples or calibration sets, which not only incur significant computational overhead during…

机器学习 · 计算机科学 2026-01-07 Jiawen Zhang , Lipeng He , Kejia Chen , Jian Lou , Jian Liu , Xiaohu Yang , Ruoxi Jia

Large Language Models (LLMs) are transforming cybersecurity by enabling intelligent, adaptive, and automated approaches to threat detection, vulnerability assessment, and incident response. With their advanced language understanding and…

密码学与安全 · 计算机科学 2025-07-21 Niveen O. Jaffal , Mohammed Alkhanafseh , David Mohaisen

Recent advancements in robot control using large language models (LLMs) have demonstrated significant potential, primarily due to LLMs' capabilities to understand natural language commands and generate executable plans in various languages.…

机器人学 · 计算机科学 2024-09-27 Guojun Chen , Xiaojing Yu , Neiwen Ling , Lin Zhong

A robot in a human-centric environment needs to account for the human's intent and future motion in its task and motion planning to ensure safe and effective operation. This requires symbolic reasoning about probable future actions and the…

机器人学 · 计算机科学 2023-11-01 Moritz A. Graule , Volkan Isler

Large language models (LLMs) have exerted a considerable impact on diverse language-related tasks in recent years. Their demonstrated state-of-the-art performance is achieved through methodologies such as zero-shot or few-shot prompting.…

计算与语言 · 计算机科学 2023-12-21 Arshad Kaji , Manan Shah

Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising results, there is still a lack of comprehensive understanding…

计算与语言 · 计算机科学 2024-10-16 Eason Chen , Danyang Wang , Luyi Xu , Chen Cao , Xiao Fang , Jionghao Lin