2,560+ academic papers on AI security, attacks, and defenses
Showing 301–320 of 1,220 papers
Clear filtersXinhao Deng, Yixiang Zhang, Jiaqing Wu +15 more
Autonomous Large Language Model (LLM) agents, exemplified by OpenClaw, demonstrate remarkable capabilities in executing complex, long-horizon tasks....
Qizhi Chen, Chao Qi, Yihong Huang +5 more
Graph-based Retrieval-Augmented Generation (GraphRAG) constructs the Knowledge Graph (KG) from external databases to enhance the timeliness and...
Zhiyu Xue, Zimo Qi, Guangliang Liu +2 more
Safety alignment aims to ensure that large language models (LLMs) refuse harmful requests by post-training on harmful queries paired with refusal...
Marc Damie, Murat Bilgehan Ertan, Domenico Essoussi +3 more
With their increasing capabilities, Large Language Models (LLMs) are now used across many industries. They have become useful tools for software...
Zixun Xiong, Gaoyi Wu, Lingfeng Yao +3 more
Communication topology is a critical factor in the utility and safety of LLM-based multi-agent systems (LLM-MAS), making it a high-value intellectual...
Panagiotis Georgios Pennas, Konstantinos Papaioannou, Marco Guarnieri +1 more
Large Language Models (LLMs) rely on optimizations like Automatic Prefix Caching (APC) to accelerate inference. APC works by reusing previously...
Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu +10 more
Instruction hierarchy (IH) defines how LLMs prioritize system, developer, user, and tool instructions under conflict, providing a concrete,...
Manit Baser, Alperen Yildiz, Dinil Mon Divakaran +1 more
The static knowledge representations of large language models (LLMs) inevitably become outdated or incorrect over time. While model-editing...
Zhengyang Shan, Jiayun Xin, Yue Zhang +1 more
Code agents powered by large language models can execute shell commands on behalf of users, introducing severe security vulnerabilities. This paper...
Shriti Priya, Julian James Stephen, Arjun Natarajan
Enterprises and organizations today increasingly deploy in-house, cloud based applications and APIs for internal operations or external customers....
Pratyay Kumar, Miguel Antonio Guirao Aguilera, Srikathyayani Srikanteswara +2 more
Model Context Protocol (MCP) servers have rapidly emerged over the past year as a widely adopted way to enable Large Language Model (LLM) agents to...
Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro, Peter Kairouz
As AI assistants become widely used, privacy-aware platforms like Anthropic's Clio have been introduced to generate insights from real-world AI use....
Jia Hu, Youcheng Sun, Pierre Olivier
Software compartmentalization breaks down an application into compartments isolated from each other: an attacker taking over a compartment will be...
Ali Raza, Gurang Gupta, Nikolay Matyunin +1 more
Warning: This article includes red-teaming experiments, which contain examples of compromised LLM responses that may be offensive or upsetting. Large...
Amir Al-Maamari
Large Language Models (LLMs) show promise for Automated Program Repair (APR), yet their effectiveness on security vulnerabilities remains poorly...
Shaswata Mitra, Raj Patel, Sudip Mittal +2 more
Multi-agent systems (MAS) powered by LLMs promise adaptive, reasoning-driven enterprise workflows, yet granting agents autonomous control over tools,...
Harry Owiredu-Ashley
Most adversarial evaluations of large language model (LLM) safety assess single prompts and report binary pass/fail outcomes, which fails to capture...
Yinpeng Wu, Yitong Chen, Lixiang Wang +3 more
Device-side Large Language Models (LLMs) have witnessed explosive growth, offering higher privacy and availability compared to cloud-side LLMs....
Alexander Erlei, Lukas Meub
As AI agents increasingly act on behalf of human stakeholders in economic settings, understanding their behavior in complex market environments...
Bo Jiang
Knowledge distillation from proprietary LLM APIs poses a growing threat to model providers, yet defenses against this attack remain fragmented and...
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