2,077+ academic papers on AI security, attacks, and defenses
Showing 101–120 of 272 papers
Clear filtersMengyuan Jin, Zehui Liao, Yong Xia
Multimodal Large Language Models (MLLMs) have shown remarkable capability in assisting disease diagnosis in medical visual question answering (VQA)....
Jiahe Guo, Xiangran Guo, Yulin Hu +8 more
Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized...
Xianya Fang, Xianying Luo, Yadong Wang +8 more
Despite the intrinsic risk-awareness of Large Language Models (LLMs), current defenses often result in shallow safety alignment, rendering models...
Zhining Liu, Tianyi Wang, Xiao Lin +9 more
Despite substantial efforts toward improving the moral alignment of Vision-Language Models (VLMs), it remains unclear whether their ethical judgments...
Saswat Das, Ferdinando Fioretto
This work addresses the computational challenge of enforcing privacy for agentic Large Language Models (LLMs), where privacy is governed by the...
Luis Lazo, Hamed Jelodar, Roozbeh Razavi-Far
In this study, we propose a homotopy-inspired prompt obfuscation framework to enhance understanding of security and safety vulnerabilities in Large...
Renmiao Chen, Yida Lu, Shiyao Cui +6 more
As Multimodal Large Language Models (MLLMs) acquire stronger reasoning capabilities to handle complex, multi-image instructions, this advancement may...
William Pan, Guiran Liu, Binrong Zhu +4 more
The rapid expansion of IoT deployments has intensified cybersecurity threats, notably Distributed Denial of Service (DDoS) attacks, characterized by...
Anudeex Shetty, Aditya Joshi, Salil S. Kanhere
Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e., text...
Xiaofeng Luo, Jiayi He, Jiawen Kang +4 more
The emergence of 6G-enabled vehicular metaverses enables Autonomous Vehicles (AVs) to operate across physical and virtual spaces through...
Jonah Ghebremichael, Saastha Vasan, Saad Ullah +6 more
Static Application Security Testing (SAST) tools using taint analysis are widely viewed as providing higher-quality vulnerability detection results...
Hao Wang, Yanting Wang, Hao Li +2 more
Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to adversarial ``jailbreak'' attacks designed to bypass...
Xingjun Ma, Yixu Wang, Hengyuan Xu +18 more
The rapid evolution of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) has driven major gains in reasoning, perception, and...
Jiawen Zhang, Yangfan Hu, Kejia Chen +7 more
Fine-tuning is an essential and pervasive functionality for applying large language models (LLMs) to downstream tasks. However, it has the potential...
Caitlin A. Stamatis, Jonah Meyerhoff, Richard Zhang +3 more
Large language models (LLMs) are increasingly used for mental health support, yet existing safety evaluations rely primarily on small,...
Zhenhua Xu, Yiran Zhao, Mengting Zhong +4 more
The rapid growth of large language models raises pressing concerns about intellectual property protection under black-box deployment. Existing...
Zhichen Zeng, Wenxuan Bao, Xiao Lin +8 more
Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation (TTA)...
Mingxiang Tao, Yu Tian, Wenxuan Tu +3 more
Federated learning (FL) addresses data privacy and silo issues in large language models (LLMs). Most prior work focuses on improving the training...
Kaiwen Zhou, Shreedhar Jangam, Ashwin Nagarajan +7 more
Large language model-based agents are rapidly evolving from simple conversational assistants into autonomous systems capable of performing complex,...
Imtiaz Ali Soomro, Hamood Ur Rehman, S. Jawad Hussain ID +3 more
The rapid proliferation of Internet of Things (IoT) devices across domains such as smart homes, industrial control systems, and healthcare networks...
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