2,560+ academic papers on AI security, attacks, and defenses
Showing 361–380 of 558 papers
Clear filtersJiayi Yuan, Jonathan Nöther, Natasha Jaques +1 more
While recent automated red-teaming methods show promise for systematically exposing model vulnerabilities, most existing approaches rely on...
Jonatan Rassekhnia
Post-quantum cryptography (PQC) is becoming essential for securing Internet of Things (IoT) and Industrial IoT (IIoT) systems against quantum-enabled...
Yow-Fu Liou, Yu-Chien Tang, Yu-Hsiang Liu +1 more
Benchmarking large language models (LLMs) is critical for understanding their capabilities, limitations, and robustness. In addition to interface...
Johannes Kaiser, Alexander Ziller, Eleni Triantafillou +2 more
Individual Differential Privacy (iDP) promises users control over their privacy, but this promise can be broken in practice. We reveal a previously...
Wenqi Zhang, Yulin Shen, Changyue Jiang +3 more
Large foundation models are integrated into Computer Use Agents (CUAs), enabling autonomous interaction with operating systems through graphical user...
Ke Xie, Xingyi Zhao, Yiwen Hu +2 more
Cellular networks are critical infrastructure supporting billions of worldwide users and safety- and mission-critical services. Vulnerabilities in...
Chutian Huang, Dake Cao, Jiacheng Ji +3 more
Background: While Large Language Models (LLMs) have achieved widespread adoption, malicious prompt engineering specifically "jailbreak attacks" poses...
Arunkumar V, Gangadharan G. R., Rajkumar Buyya
Artificial Intelligence is moving from models that only generate text to Agentic AI, where systems behave as autonomous entities that can perceive,...
Huanyi Ye, Jiale Guo, Ziyao Liu +1 more
RAG has emerged as a key technique for enhancing response quality of LLMs without high computational cost. In traditional architectures, RAG services...
Yixuan Du, Chenxiao Yu, Haoyan Xu +3 more
Vision-Language Models (VLMs) are rapidly replacing unimodal encoders in modern retrieval and recommendation systems. While their capabilities are...
Xiaomei Zhang, Zhaoxi Zhang, Leo Yu Zhang +3 more
Visual token compression is widely adopted to improve the inference efficiency of Large Vision-Language Models (LVLMs), enabling their deployment in...
Jun Liu, Leo Yu Zhang, Fengpeng Li +2 more
Hard-label black-box settings, where only top-1 predicted labels are observable, pose a fundamentally constrained yet practically important feedback...
Jun Liu, Leo Yu Zhang, Fengpeng Li +2 more
Hard-label black-box settings, where only top-1 predicted labels are observable, pose a fundamentally constrained yet practically important feedback...
David Otero, Javier Parapar
Query expansion is a long-standing technique to mitigate vocabulary mismatch in ad hoc Information Retrieval. Pseudo-relevance feedback methods, such...
Yuanxiang Liu, Songze Li, Xiaoke Guo +4 more
Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations....
Haoze Guo, Ziqi Wei
Retrieval-augmented generation (RAG) systems put more and more emphasis on grounding their responses in user-generated content found on the Web,...
Sara AlMahri, Liming Xu, Alexandra Brintrup
Modern supply chains are increasingly exposed to disruptions from geopolitical events, demand shocks, trade restrictions, to natural disasters. While...
Greta Dolcetti, Giulio Zizzo, Sergio Maffeis
We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three...
Shaznin Sultana, Sadia Afreen, Nasir U. Eisty
Context: Traditional software security analysis methods struggle to keep pace with the scale and complexity of modern codebases, requiring...
Ziqi Ding, Yunfeng Wan, Wei Song +7 more
CAPTCHAs are widely used by websites to block bots and spam by presenting challenges that are easy for humans but difficult for automated programs to...
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