2,583+ academic papers on AI security, attacks, and defenses
Showing 581–600 of 2,583 papers
Xiaobing Sun, Perry Lam, Shaohua Li +4 more
Modern LLMs employ safety mechanisms that extend beyond surface-level input filtering to latent semantic representations and generation-time...
Zhouwei Zhai, Mengxiang Chen, Anmeng Zhang
Large language models offer transformative potential for e-commerce search by enabling intent-aware recommendations. However, their industrial...
Cosimo Spera
Customer service automation is undergoing a structural transformation. The dominant paradigm is shifting from scripted chatbots and single-agent...
Amira Guesmi, Muhammad Shafique
Vision-language models (VLMs) have recently shown remarkable capabilities in visual understanding and generation, but remain vulnerable to...
Roberto Morabito, Mallik Tatipamula
The Internet has evolved by progressively expanding what humanity connects: first computers, then people, and later billions of devices through the...
Ce Zhang, Jinxi He, Junyi He +2 more
Multi-modal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of visual reasoning tasks, yet their vulnerability...
Lingyu Li, Yan Teng, Yingchun Wang
Existing behavioral alignment techniques for Large Language Models (LLMs) often neglect the discrepancy between surface compliance and internal...
Yihao Zhang, Zeming Wei, Xiaokun Luan +7 more
Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security...
Yihao Zhang, Zeming Wei, Xiaokun Luan +7 more
Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security...
Trishita Dhara, Siddhesh Sheth
Large language models are increasingly deployed in settings where relevant information is embedded within long and noisy contexts. Despite this,...
Zhenheng Tang, Xiang Liu, Qian Wang +3 more
As Large Language Models (LLMs) become more powerful and autonomous, they increasingly face conflicts and dilemmas in many scenarios. We first...
Simone Aonzo, Merve Sahin, Aurélien Francillon +1 more
Artificial intelligence (AI) systems are increasingly adopted as tool-using agents that can plan, observe their environment, and take actions over...
Taeyun Roh, Wonjune Jang, Junha Jung +1 more
Large language model agents heavily rely on external memory to support knowledge reuse and complex reasoning tasks. Yet most memory systems store...
Vanshaj Khattar, Md Rafi ur Rashid, Moumita Choudhury +4 more
Test-time training (TTT) has recently emerged as a promising method to improve the reasoning abilities of large language models (LLMs), in which the...
Kai Wang, Biaojie Zeng, Zeming Wei +7 more
With the rapid development of LLM-based multi-agent systems (MAS), their significant safety and security concerns have emerged, which introduce novel...
Yu Pan, Wenlong Yu, Tiejun Wu +4 more
Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks. However, they remain highly susceptible to...
Mateusz Dziemian, Maxwell Lin, Xiaohan Fu +28 more
LLM based agents are increasingly deployed in high stakes settings where they process external data sources such as emails, documents, and code...
Ye Wang, Jing Liu, Toshiaki Koike-Akino
The safety and reliability of vision-language models (VLMs) are a crucial part of deploying trustworthy agentic AI systems. However, VLMs remain...
Yuhuan Liu, Haitian Zhong, Xinyuan Xia +3 more
Large Language Models (LLMs) often suffer from catastrophic forgetting and collapse during sequential knowledge editing. This vulnerability stems...
Zhenlin Xu, Xiaogang Zhu, Yu Yao +2 more
Modern agentic systems allow Large Language Model (LLM) agents to tackle complex tasks through extensive tool usage, forming structured control flows...
Get breaking CVE alerts, compliance reports (ISO 42001, EU AI Act), and CISO risk assessments for your AI/ML stack.
Start 14-Day Free Trial
AI Threat Alert