2,560+ academic papers on AI security, attacks, and defenses
Showing 481–500 of 736 papers
Clear filtersGary Ackerman, Zachary Kallenborn, Anna Wetzel +7 more
The potential for rapidly-evolving frontier artificial intelligence (AI) models, especially large language models (LLMs), to facilitate bioterrorism...
Md Nazmul Haque, Elizabeth Lin, Lawrence Arkoh +2 more
Large Language Models for code (LLMs4Code) are increasingly used to generate software artifacts, including library and package recommendations in...
Lukas Johannes Möller
The escalating sophistication and variety of cyber threats have rendered static honeypots inadequate, necessitating adaptive, intelligence-driven...
Jordan Taylor, Sid Black, Dillon Bowen +10 more
Future AI systems could conceal their capabilities ('sandbagging') during evaluations, potentially misleading developers and auditors. We...
Sangha Park, Seungryong Yoo, Jisoo Mok +1 more
Although Multimodal Large Language Models (MLLMs) have advanced substantially, they remain vulnerable to object hallucination caused by language...
Alisha Ukani, Hamed Haddadi, Ali Shahin Shamsabadi +1 more
This paper presents a systematic evaluation of the privacy behaviors and attributes of eight recent, popular browser agents. Browser agents are...
JV Roig
We investigate how large language models (LLMs) fail when operating as autonomous agents with tool-use capabilities. Using the Kamiwaza Agentic Merit...
Qiwei Tian, Chenhao Lin, Zhengyu Zhao +1 more
To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs against...
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...
Cheng Cheng, Jinqiu Yang
Code-focused Large Language Models (LLMs), such as CodeX and Star-Coder, have demonstrated remarkable capabilities in enhancing developer...
Caleb Gross
Security research is fundamentally a problem of resource constraint and consequent prioritization. There is simply too much attack surface and too...
Xiuyuan Chen, Jian Zhao, Yuxiang He +10 more
While the deployment of large language models (LLMs) in high-value industries continues to expand, the systematic assessment of their safety against...
Ashish Hooda, Mihai Christodorescu, Chuangang Ren +3 more
Machine learning (ML) models for code clone detection determine whether two pieces of code are semantically equivalent, which in turn is a key...
Feijiang Han
Malicious WebShells pose a significant and evolving threat by compromising critical digital infrastructures and endangering public services in...
Chenlin Xu, Lei Zhang, Lituan Wang +5 more
Due to the scarcity of annotated data and the substantial computational costs of model, conventional tuning methods in medical image segmentation...
Yizhou Zhao, Zhiwei Steven Wu, Adam Block
Watermarking aims to embed hidden signals in generated text that can be reliably detected when given access to a secret key. Open-weight language...
Tengyun Ma, Jiaqi Yao, Daojing He +4 more
Large Language Models (LLMs) have emerged as powerful tools for diverse applications. However, their uniform token processing paradigm introduces...
Songwen Zhao, Danqing Wang, Kexun Zhang +3 more
Vibe coding is a new programming paradigm in which human engineers instruct large language model (LLM) agents to complete complex coding tasks with...
Junyu Wang, Changjia Zhu, Yuanbo Zhou +3 more
This paper studies how multimodal large language models (MLLMs) undermine the security guarantees of visual CAPTCHA. We identify the attack surface...
Han Luo, Guy Laban
Large language models (LLMs) now mediate many web-based mental-health, crisis, and other emotionally sensitive services, yet their psychosocial...
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