2,529+ academic papers on AI security, attacks, and defenses
Showing 1–20 of 26 papers
Clear filtersJoel Rorseth, Parke Godfrey, Lukasz Golab +2 more
This paper demonstrates RUBEN, an interactive tool for discovering minimal rules to explain the outputs of retrieval-augmented large language models...
Tim Van hamme, Thomas Vissers, Javier Carnerero-Cano +4 more
LLMs are increasingly deployed as autonomous agents with access to tools, databases, and external services, yet practitioners (across different...
Yu-Hsiang Liu, Yu-Chien Tang, An-Zi Yen
Training AI agents to proactively assist humans in daily activities, from routine household tasks to urgent safety situations, requires large-scale...
Michael A. Riegler, Inga Strümke
We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory,...
Chengjie Wang, Jingzheng Wu, Xiang Ling +2 more
Large language models (LLMs) are now largely involved in software development workflows, and the code they generate routinely includes third-party...
Zhaorun Chen, Xun Liu, Haibo Tong +14 more
AI agents are increasingly deployed across diverse domains to automate complex workflows through long-horizon and high-stakes action executions. Due...
Haoyu Zhang, Mohammad Zandsalimy, Shanu Sushmita
Large language models (LLMs) employ safety mechanisms to prevent harmful outputs, yet these defenses primarily rely on semantic pattern matching. We...
Kerri Prinos, Lilianne Brush, Cameron Denton +5 more
Agentic systems involved in high-stake decision-making under adversarial pressure need formal guarantees not offered by existing approaches....
Mingming Zha, Xiaofeng Wang
Autonomous LLM agents operate as long-running processes with persistent workspaces, memory files, scheduled task state, and messaging integrations....
Neha Nagaraja, Hayretdin Bahsi, Carlo R. da Cunha
As large language models are integrated into autonomous robotic systems for task planning and control, compromised inputs or unsafe model outputs can...
Weiyi Kong, Ahmad Mohammad Saber, Amr Youssef +1 more
In modern energy systems, industrial control systems (ICS) and power-system SCADA require intrusion detection that is not only accurate but also...
Zheng Wu, Yi Hua, Zhaoyuan Huang +8 more
The evolution of Multimodal Large Language Models (MLLMs) has shifted the focus from text generation to active behavioral execution, particularly via...
Jeffrey Wong, Antoine Creux
Create an idea, prototype it, evaluate if users like it, then learn. It is the circle of business. If AI can operate in all parts of the circle, it...
Kato Mivule
This paper extends the Classification Error Gauge (x-CEG) framework, originally developed for measuring the privacy-utility trade-off in tabular...
Yuchuan Zhao, Tong Chen, Junliang Yu +3 more
Large language model-powered sequential recommender systems (LLM-SRSs) have recently demonstrated remarkable performance, enabling recommendations...
Run Hao, Zhuoran Tan
Model Context Protocol (MCP) is increasingly adopted for tool-integrated LLM agents, but its multi-layer design and third-party server ecosystem...
Mikko Lempinen, Joni Kemppainen, Niklas Raesalmi
As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of...
Yingyong Hou, Xinyuan Lao, Huimei Wang +10 more
Background: Agent skills are increasingly deployed as modular, reusable capability units in AI agent systems. Medical research agent skills require...
Jiamin Chang, Minhui Xue, Ruoxi Sun +3 more
Recent advances in embodied Vision-Language Agentic Systems (VLAS), powered by large vision-language models (LVLMs), enable AI systems to perceive...
Jiacheng Liang, Yao Ma, Tharindu Kumarage +5 more
Reinforcement Learning from Human Feedback (RLHF) is central to aligning Large Language Models (LLMs), yet it introduces a critical vulnerability: an...
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