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With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting and discriminatory content, reflect incorrect social values,…

计算与语言 · 计算机科学 2023-04-21 Hao Sun , Zhexin Zhang , Jiawen Deng , Jiale Cheng , Minlie Huang

Large Language Models increasingly power critical infrastructure from healthcare to finance, yet their vulnerability to adversarial manipulation threatens system integrity and user safety. Despite growing deployment, no comprehensive…

密码学与安全 · 计算机科学 2026-03-19 Taiwo Onitiju , Iman Vakilinia

Large Language Models (LLMs) have rapidly evolved over the past few years and are currently evaluated for their efficacy within the domain of offensive cyber-security. While initial forays showcase the potential of LLMs to enhance security…

密码学与安全 · 计算机科学 2025-06-11 Andreas Happe , Jürgen Cito

In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications. As the use of LLMs expands, precisely estimating the uncertainty in their predictions has become crucial.…

Large Language Models (LLMs) increasingly support applications in a wide range of domains, some with potential high societal impact such as biomedicine, yet their reliability in realistic use cases is under-researched. In this work we…

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

Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to faithfully express their knowledge. Despite promising, current…

计算与语言 · 计算机科学 2024-09-30 Siheng Li , Cheng Yang , Taiqiang Wu , Chufan Shi , Yuji Zhang , Xinyu Zhu , Zesen Cheng , Deng Cai , Mo Yu , Lemao Liu , Jie Zhou , Yujiu Yang , Ngai Wong , Xixin Wu , Wai Lam

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these…

计算与语言 · 计算机科学 2025-07-08 Jianchao Ji , Yutong Chen , Mingyu Jin , Wujiang Xu , Wenyue Hua , Yongfeng Zhang

Prompt injection attacks exploit vulnerabilities in large language models (LLMs) to manipulate the model into unintended actions or generate malicious content. As LLM integrated applications gain wider adoption, they face growing…

密码学与安全 · 计算机科学 2024-01-03 Daniel Wankit Yip , Aysan Esmradi , Chun Fai Chan

Evaluations of Large Language Models (LLMs) on knowledge-intensive tasks and factual accuracy often focus on high-resource languages primarily because datasets for low-resource languages (LRLs) are scarce. In this paper, we present Uhura --…

Large Language Models (LLMs) have demonstrated potential in cybersecurity applications but have also caused lower confidence due to problems like hallucinations and a lack of truthfulness. Existing benchmarks provide general evaluations but…

While the widespread deployment of Large Language Models (LLMs) holds great potential for society, their vulnerabilities to adversarial manipulation and exploitation can pose serious safety, security, and ethical risks. As new threats…

密码学与安全 · 计算机科学 2025-09-29 Charankumar Akiri , Harrison Simpson , Kshitiz Aryal , Aarav Khanna , Maanak Gupta

Recent advancements in multimodal large language models for video understanding (videoLLMs) have enhanced their capacity to process complex spatiotemporal data. However, challenges such as factual inaccuracies, harmful content, biases,…

计算机视觉与模式识别 · 计算机科学 2025-11-27 Youze Wang , Zijun Chen , Ruoyu Chen , Shishen Gu , Wenbo Hu , Jiayang Liu , Yinpeng Dong , Hang Su , Jun Zhu , Meng Wang , Richang Hong

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

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

Large language models (LLMs) are increasingly applied to materials science questions, including literature comprehension, property prediction, materials discovery and alloy design. At the same time, a wide range of physics-based…

材料科学 · 物理学 2025-12-17 Siyu Liu , Bo Hu , Beilin Ye , Jiamin Xu , David J. Srolovitz , Tongqi Wen

Several recent works have argued that Large Language Models (LLMs) can be used to tame the data deluge in the cybersecurity field, by improving the automation of Cyber Threat Intelligence (CTI) tasks. This work presents an evaluation…

密码学与安全 · 计算机科学 2025-11-13 Emanuele Mezzi , Fabio Massacci , Katja Tuma

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional…

Large Language Models (LLMs) can engage in human-looking conversational exchanges. Although conversations can elicit trust between users and LLMs, scarce empirical research has examined trust formation in human-LLM contexts, beyond LLMs'…

人机交互 · 计算机科学 2025-03-06 Edoardo Sebastiano De Duro , Giuseppe Alessandro Veltri , Hudson Golino , Massimo Stella

Large language models (LLMs) have become increasingly embedded in organizational workflows. This has raised concerns over their energy consumption, financial costs, and data sovereignty. While performance benchmarks often celebrate…

计算与语言 · 计算机科学 2026-05-19 Jennifer Haase , Finn Klessascheck , Jan Mendling , Sebastian Pokutta