2,560+ academic papers on AI security, attacks, and defenses
Showing 561–580 of 879 papers
Clear filtersReachal Wang, Yuqi Jia, Neil Zhenqiang Gong
Prompt injection attacks aim to contaminate the input data of an LLM to mislead it into completing an attacker-chosen task instead of the intended...
Joshua Ward, Bochao Gu, Chi-Hua Wang +1 more
Large Language Models (LLMs) have recently demonstrated remarkable performance in generating high-quality tabular synthetic data. In practice, two...
Dyna Soumhane Ouchebara, Stéphane Dupont
The significant increase in software production, driven by the acceleration of development cycles over the past two decades, has led to a steady rise...
Yinan Zhong, Qianhao Miao, Yanjiao Chen +3 more
Large Language Models (LLMs) have been integrated into many applications (e.g., web agents) to perform more sophisticated tasks. However,...
Tailun Chen, Yu He, Yan Wang +9 more
Retrieval-Augmented Generation (RAG) systems enhance LLMs with external knowledge but introduce a critical attack surface: corpus poisoning. While...
Zafaryab Haider, Md Hafizur Rahman, Shane Moeykens +2 more
Hard-to-detect hardware bit flips, from either malicious circuitry or bugs, have already been shown to make transformers vulnerable in non-generative...
Jinghao Wang, Ping Zhang, Carter Yagemann
Medical Large Language Models (LLMs) are increasingly deployed for clinical decision support across diverse specialties, yet systematic evaluation of...
Stephan Carney, Soham Hans, Sofia Hirschmann +4 more
Adversaries (hackers) attempting to infiltrate networks frequently face uncertainty in their operational environments. This research explores the...
Xiqiao Xiong, Ouxiang Li, Zhuo Liu +5 more
Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment....
Max Zhang, Derek Liu, Kai Zhang +2 more
Large language models (LLMs) are increasingly deployed worldwide, yet their safety alignment remains predominantly English-centric. This allows for...
Yunzhe Li, Jianan Wang, Hongzi Zhu +3 more
Large Language Models (LLMs) have become foundational components in a wide range of applications, including natural language understanding and...
Richard Young
Despite substantial investment in safety alignment, the vulnerability of large language models to sophisticated multi-turn adversarial attacks...
Songping Wang, Rufan Qian, Yueming Lyu +5 more
Image-to-Video (I2V) generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the...
Xiaojun Jia, Jie Liao, Qi Guo +11 more
Recent advances in multi-modal large language models (MLLMs) have enabled unified perception-reasoning capabilities, yet these systems remain highly...
Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +3 more
The Model Context Protocol (MCP) enables Large Language Models to integrate external tools through structured descriptors, increasing autonomy in...
Chenyu Zhang, Yiwen Ma, Lanjun Wang +3 more
Text-to-image~(T2I) models commonly incorporate defense mechanisms to prevent the generation of sensitive images. Unfortunately, recent jailbreaking...
Yuhang Huang, Junchao Li, Boyang Ma +6 more
Embodied AI systems integrate language models with real world sensing, mobility, and cloud connected mobile apps. Yet while model jailbreaks have...
Caleb Gross
Security research is fundamentally a problem of resource constraint and consequent prioritization. There is simply too much attack surface and too...
Shiji Zhao, Shukun Xiong, Yao Huang +7 more
Multimodal Large Language Models (MLLMs) are widely used in various fields due to their powerful cross-modal comprehension and generation...
Weikai Lu, Ziqian Zeng, Kehua Zhang +5 more
Multimodal Large Language Models (MLLMs) are increasingly vulnerable to multimodal Indirect Prompt Injection (IPI) attacks, which embed malicious...
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