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Large Language Models (LLMs) are gearing up to surpass human creativity. The veracity of the statement needs careful consideration. In recent developments, critical questions arise regarding the authenticity of human work and the…

Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Due to their training on internet-sourced datasets, LLMs can sometimes generate objectionable content, necessitating…

计算与语言 · 计算机科学 2024-11-15 Leyang Hu , Boran Wang

Large Language Models (LLMs) are increasingly deployed in sensitive domains including healthcare, legal services, and confidential communications, where privacy is paramount. This paper introduces Whisper Leak, a side-channel attack that…

密码学与安全 · 计算机科学 2025-11-06 Geoff McDonald , Jonathan Bar Or

Large Language Models (LLMs) have become increasingly popular for their advanced text generation capabilities across various domains. However, like any software, they face security challenges, including the risk of 'jailbreak' attacks that…

密码学与安全 · 计算机科学 2024-01-31 Jie Li , Yi Liu , Chongyang Liu , Ling Shi , Xiaoning Ren , Yaowen Zheng , Yang Liu , Yinxing Xue

Large-scale web-scraped text corpora used to train general-purpose AI models often contain harmful demographic-targeted social biases, creating a regulatory need for data auditing and developing scalable bias-detection methods. Although…

计算与语言 · 计算机科学 2026-04-10 Ayan Majumdar , Feihao Chen , Jinghui Li , Xiaozhen Wang

Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned and clean texts. Although recent studies introduce LLMs to…

计算与语言 · 计算机科学 2025-04-22 Zhengxian Wu , Juan Wen , Wanli Peng , Ziwei Zhang , Yinghan Zhou , Yiming Xue

Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are susceptible to adversarial attacks where malicious users can…

Recently, Large Language Model (LLM)-empowered recommender systems (RecSys) have brought significant advances in personalized user experience and have attracted considerable attention. Despite the impressive progress, the research question…

密码学与安全 · 计算机科学 2025-04-25 Liang-bo Ning , Shijie Wang , Wenqi Fan , Qing Li , Xin Xu , Hao Chen , Feiran Huang

The widespread adoption of large language models (LLMs) has made it difficult to distinguish human writing from machine-produced text in many real applications. Detectors that were effective for one generation of models tend to degrade when…

计算与语言 · 计算机科学 2025-12-09 Sepyan Purnama Kristanto , Lutfi Hakim , Dianni Yusuf

Large Language Models (LLMs) remain vulnerable to jailbreak attacks that bypass their safety mechanisms. Existing attack methods are fixed or specifically tailored for certain models and cannot flexibly adjust attack strength, which is…

密码学与安全 · 计算机科学 2024-10-08 Yiting Dong , Guobin Shen , Dongcheng Zhao , Xiang He , Yi Zeng

Despite recent advances, Large Language Models remain vulnerable to jailbreak attacks that bypass alignment safeguards and elicit harmful outputs. While prior research has proposed various attack strategies differing in human readability…

计算与语言 · 计算机科学 2025-10-28 Havva Alizadeh Noughabi , Julien Serbanescu , Fattane Zarrinkalam , Ali Dehghantanha

Large Language Models (LLMs) can generate highly persuasive text, raising concerns about their misuse for propaganda, manipulation, and other harmful purposes. This leads us to our central question: Is LLM-generated persuasion more…

计算与语言 · 计算机科学 2026-04-22 Arkadiusz Modzelewski , Paweł Golik , Anna Kołos , Giovanni Da San Martino

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 Model (LLMs) can be used to write or modify documents, presenting a challenge for understanding the intent behind their use. For example, benign uses may involve using LLM on a human-written document to improve its grammar or…

计算与语言 · 计算机科学 2025-09-22 Yitong Wang , Zhongping Zhang , Margherita Piana , Zheng Zhou , Peter Gerstoft , Bryan A. Plummer

The generalization capabilities of Large Language Models (LLMs) have led to their widespread deployment across various applications. However, this increased adoption has introduced several security threats, notably in the forms of…

密码学与安全 · 计算机科学 2025-08-04 Francesco Panebianco , Stefano Bonfanti , Francesco Trovò , Michele Carminati

Large Language Model (LLM)-generated data is increasingly used in software analytics, but it is unclear how this data compares to human-written data, particularly when models are exposed to adversarial scenarios. Adversarial attacks can…

软件工程 · 计算机科学 2025-05-07 Md. Abdul Awal , Mrigank Rochan , Chanchal K. Roy

Large language models (LLMs) possess strong semantic understanding, driving significant progress in data mining applications. This is further enhanced by large reasoning models (LRMs), which provide explicit multi-step reasoning traces. On…

机器学习 · 计算机科学 2026-04-07 Aobo Chen , Chenxu Zhao , Chenglin Miao , Mengdi Huai

The dissemination of Large Language Models (LLMs), trained at scale, and endowed with powerful text-generating abilities, has made it easier for all to produce harmful, toxic, faked or forged content. In response, various proposals have…

计算与语言 · 计算机科学 2025-06-12 Matthieu Dubois , François Yvon , Pablo Piantanida

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

计算与语言 · 计算机科学 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

Phishing has become a prominent risk in modern cybersecurity, often used to bypass technological defences by exploiting predictable human behaviour. Warning dialogues are a standard mitigation measure, but the lack of explanatory clarity…

密码学与安全 · 计算机科学 2025-12-16 Federico Maria Cau , Giuseppe Desolda , Francesco Greco , Lucio Davide Spano , Luca Viganò