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The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds that language models can use tools in ways that contradict the interests or explicit instructions…

Machine Learning · Computer Science 2026-04-24 Kushal Agrawal , Frank Xiao , Guido Bergman , Asa Cooper Stickland

Many studies have demonstrated that large language models (LLMs) can produce harmful responses, exposing users to unexpected risks when LLMs are deployed. Previous studies have proposed comprehensive taxonomies of the risks posed by LLMs,…

Computation and Language · Computer Science 2024-08-06 Yuxia Wang , Zenan Zhai , Haonan Li , Xudong Han , Lizhi Lin , Zhenxuan Zhang , Jingru Zhao , Preslav Nakov , Timothy Baldwin

Jailbreak attacks pose a serious threat to the safety of Large Language Models (LLMs) by crafting adversarial prompts that bypass alignment mechanisms, causing the models to produce harmful, restricted, or biased content. In this paper, we…

Machine Learning · Computer Science 2025-08-22 Xiangman Li , Xiaodong Wu , Qi Li , Jianbing Ni , Rongxing Lu

The rapid development and deployment of large language models (LLMs) have introduced a new frontier in artificial intelligence, marked by unprecedented capabilities in natural language understanding and generation. However, the increasing…

Artificial Intelligence · Computer Science 2024-12-25 Dan Shi , Tianhao Shen , Yufei Huang , Zhigen Li , Yongqi Leng , Renren Jin , Chuang Liu , Xinwei Wu , Zishan Guo , Linhao Yu , Ling Shi , Bojian Jiang , Deyi Xiong

The recent surge in jailbreaking attacks has revealed significant vulnerabilities in Large Language Models (LLMs) when exposed to malicious inputs. While various defense strategies have been proposed to mitigate these threats, there has…

Computation and Language · Computer Science 2025-02-24 Tianlong Li , Zhenghua Wang , Wenhao Liu , Muling Wu , Shihan Dou , Changze Lv , Xiaohua Wang , Xiaoqing Zheng , Xuanjing Huang

Large Language Models (LLMs) have significantly advanced natural language processing (NLP) tasks but also pose ethical and societal risks due to their propensity to generate harmful content. Existing methods have limitations, including the…

Computation and Language · Computer Science 2025-05-22 Ximing Dong , Dayi Lin , Shaowei Wang , Ahmed E. Hassan

The advancement of large language models (LLMs) has significantly enhanced the ability to effectively tackle various downstream NLP tasks and unify these tasks into generative pipelines. On the one hand, powerful language models, trained on…

Computation and Language · Computer Science 2024-10-01 Haoran Li , Yulin Chen , Jinglong Luo , Jiecong Wang , Hao Peng , Yan Kang , Xiaojin Zhang , Qi Hu , Chunkit Chan , Zenglin Xu , Bryan Hooi , Yangqiu Song

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…

Computation and Language · Computer Science 2024-07-08 Shangbin Feng , Herun Wan , Ningnan Wang , Zhaoxuan Tan , Minnan Luo , Yulia Tsvetkov

The rapid evolution of network infrastructure is bringing new challenges and opportunities for efficient network management, optimization, and security. With very large monitoring databases becoming expensive to explore, the use of AI and…

Networking and Internet Architecture · Computer Science 2025-07-31 Hong-Jun Yoon , Mariam Kiran , Danial Ebling , Joe Breen

Large language models (LLMs) have become increasingly sophisticated, leading to widespread deployment in sensitive applications where safety and reliability are paramount. However, LLMs have inherent risks accompanying them, including bias,…

Cryptography and Security · Computer Science 2024-06-21 Suriya Ganesh Ayyamperumal , Limin Ge

Multimodal large language models (MLLMs) have revolutionized vision-language understanding but remain vulnerable to multimodal jailbreak attacks, where adversarial inputs are meticulously crafted to elicit harmful or inappropriate…

Computation and Language · Computer Science 2025-02-03 Sejoon Oh , Yiqiao Jin , Megha Sharma , Donghyun Kim , Eric Ma , Gaurav Verma , Srijan Kumar

In the digital world, memes present a unique challenge for content moderation due to their potential to spread harmful content. Although detection methods have improved, proactive solutions such as intervention are still limited, with…

Computation and Language · Computer Science 2024-06-11 Prince Jha , Raghav Jain , Konika Mandal , Aman Chadha , Sriparna Saha , Pushpak Bhattacharyya

Large Language Models (LLMs) have gained considerable traction within the Software Engineering (SE) community, impacting various SE tasks from code completion to test generation, from program repair to code summarization. Despite their…

Software Engineering · Computer Science 2024-01-09 June Sallou , Thomas Durieux , Annibale Panichella

Large language models (LLMs) have achieved record adoption in a short period of time across many different sectors including high importance areas such as education [4] and healthcare [23]. LLMs are open-ended models trained on diverse data…

Cryptography and Security · Computer Science 2024-12-24 Herve Debar , Sven Dietrich , Pavel Laskov , Emil C. Lupu , Eirini Ntoutsi

Large language models (LLMs) are popular for high-quality text generation but can produce harmful content, even when aligned with human values through reinforcement learning. Adversarial prompts can bypass their safety measures. We propose…

Computation and Language · Computer Science 2024-05-03 Mansi Phute , Alec Helbling , Matthew Hull , ShengYun Peng , Sebastian Szyller , Cory Cornelius , Duen Horng Chau

Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet remain vulnerable to indirect prompt injection. Adversaries exploit this weakness by…

Cryptography and Security · Computer Science 2026-05-12 Wei Zhao , Zhe Li , Peixin Zhang , Jun Sun

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…

Cryptography and Security · Computer Science 2025-08-04 Francesco Panebianco , Stefano Bonfanti , Francesco Trovò , Michele Carminati

The proliferation of large language models (LLMs) has sparked widespread and general interest due to their strong language generation capabilities, offering great potential for both industry and research. While previous research delved into…

Artificial Intelligence · Computer Science 2024-07-09 Lukas Struppek , Minh Hieu Le , Dominik Hintersdorf , Kristian Kersting

The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts raises many concerns regarding their misuse. Previous research has shown that LLMs can be…

Computation and Language · Computer Science 2025-07-28 Aneta Zugecova , Dominik Macko , Ivan Srba , Robert Moro , Jakub Kopal , Katarina Marcincinova , Matus Mesarcik

The spread of fake news has emerged as a critical challenge, undermining trust and posing threats to society. In the era of Large Language Models (LLMs), the capability to generate believable fake content has intensified these concerns. In…

Computation and Language · Computer Science 2023-09-19 Jinyan Su , Terry Yue Zhuo , Jonibek Mansurov , Di Wang , Preslav Nakov
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