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This position paper proposes a novel approach to advancing NLP security by leveraging Large Language Models (LLMs) as engines for generating diverse adversarial attacks. Building upon recent work demonstrating LLMs' effectiveness in…

人工智能 · 计算机科学 2024-10-25 Sudarshan Srinivasan , Maria Mahbub , Amir Sadovnik

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

Recent advances in large language models (LLMs) have unlocked novel opportunities for machine learning applications in the financial domain. These models have demonstrated remarkable capabilities in understanding context, processing vast…

综合金融 · 定量金融 2024-06-19 Yuqi Nie , Yaxuan Kong , Xiaowen Dong , John M. Mulvey , H. Vincent Poor , Qingsong Wen , Stefan Zohren

Large language models (LLMs) have revolutionized how we interact with machines. However, this technological advancement has been paralleled by the emergence of "Mallas," malicious services operating underground that exploit LLMs for…

计算与语言 · 计算机科学 2024-08-12 Garrett Crumrine , Izzat Alsmadi , Jesus Guerrero , Yuvaraj Munian

The past decade has been transformative for mental health research and practice. The ability to harness large repositories of data, whether from electronic health records (EHR), mobile devices, or social media, has revealed a potential for…

计算与语言 · 计算机科学 2023-11-28 Munmun De Choudhury , Sachin R. Pendse , Neha Kumar

Large language models (LLMs) are now highly capable at a diverse range of tasks. This paper studies whether or not GPT-4, one such LLM, is capable of assisting researchers in the field of adversarial machine learning. As a case study, we…

密码学与安全 · 计算机科学 2023-07-28 Nicholas Carlini

Large Language Model (LLM) systems are inherently compositional, with individual LLM serving as the core foundation with additional layers of objects such as plugins, sandbox, and so on. Along with the great potential, there are also…

密码学与安全 · 计算机科学 2024-03-01 Fangzhou Wu , Ning Zhang , Somesh Jha , Patrick McDaniel , Chaowei Xiao

Large language models (LLMs) are promising tools for supporting security management tasks, such as incident response planning. However, their unreliability and tendency to hallucinate remain significant challenges. In this paper, we address…

人工智能 · 计算机科学 2026-02-06 Kim Hammar , Tansu Alpcan , Emil Lupu

Large Language Models (LLMs), which bridge the gap between human language understanding and complex problem-solving, achieve state-of-the-art performance on several NLP tasks, particularly in few-shot and zero-shot settings. Despite the…

密码学与安全 · 计算机科学 2025-01-07 Shuai Zhao , Meihuizi Jia , Zhongliang Guo , Leilei Gan , Xiaoyu Xu , Xiaobao Wu , Jie Fu , Yichao Feng , Fengjun Pan , Luu Anh Tuan

This paper assesses the potential for the large language models (LLMs) GPT-4 and GPT-3.5 to aid in deriving insight from education feedback surveys. Exploration of LLM use cases in education has focused on teaching and learning, with less…

计算与语言 · 计算机科学 2024-06-28 Michael J. Parker , Caitlin Anderson , Claire Stone , YeaRim Oh

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

The integration of Large Language Models (LLMs) and Federated Learning (FL) presents a promising solution for joint training on distributed data while preserving privacy and addressing data silo issues. However, this emerging field, known…

密码学与安全 · 计算机科学 2025-05-15 Wenhao Jiang , Yuchuan Luo , Guilin Deng , Silong Chen , Xu Yang , Shihong Wu , Xinwen Gao , Lin Liu , Shaojing Fu

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

人工智能 · 计算机科学 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, leading to the emergence of a series of agents that use LLMs as…

人工智能 · 计算机科学 2024-11-15 Yuyou Gan , Yong Yang , Zhe Ma , Ping He , Rui Zeng , Yiming Wang , Qingming Li , Chunyi Zhou , Songze Li , Ting Wang , Yunjun Gao , Yingcai Wu , Shouling Ji

Large language models (LLMs) are currently at the forefront of intertwining artificial intelligence (AI) systems with human communication and everyday life. Thus, aligning them with human values is of great importance. However, given the…

计算与语言 · 计算机科学 2024-06-06 Thilo Hagendorff

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit…

计算与语言 · 计算机科学 2023-10-20 Katikapalli Subramanyam Kalyan

In this paper, we explore the potential of Large Language Models (LLMs) to reason about threats, generate information about tools, and automate cyber campaigns. We begin with a manual exploration of LLMs in supporting specific…

密码学与安全 · 计算机科学 2023-10-12 Stephen Moskal , Sam Laney , Erik Hemberg , Una-May O'Reilly

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