2,589+ academic papers on AI security, attacks, and defenses
Showing 1381–1400 of 2,589 papers
Abdelaziz Bounhar, Rania Hossam Elmohamady Elbadry, Hadi Abdine +3 more
Steering Large Language Models (LLMs) through activation interventions has emerged as a lightweight alternative to fine-tuning for alignment and...
Zhenhua Xu, Yiran Zhao, Mengting Zhong +4 more
The rapid growth of large language models raises pressing concerns about intellectual property protection under black-box deployment. Existing...
Zhichen Zeng, Wenxuan Bao, Xiao Lin +8 more
Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation (TTA)...
Aarya Doshi, Yining Hong, Congying Xu +3 more
Large language model (LLM)-based AI agents extend LLM capabilities by enabling access to tools such as data sources, APIs, search engines, code...
Mohammed Himayath Ali, Mohammed Aqib Abdullah, Mohammed Mudassir Uddin +1 more
Large Language Models have emerged as transformative tools for Security Operations Centers, enabling automated log analysis, phishing triage, and...
Dongryeol Lee, Yerin Hwang, Taegwan Kang +3 more
While large language models (LLMs) are increasingly used as automatic judges for question answering (QA) and other reference-conditioned evaluation...
Ruiqi Li, Zhiqiang Wang, Yunhao Yao +1 more
To standardize interactions between LLM-based agents and their environments, the Model Context Protocol (MCP) was proposed and has since been widely...
Xinyi Wu, Geng Hong, Yueyue Chen +5 more
Web agents, powered by large language models (LLMs), are increasingly deployed to automate complex web interactions. The rise of open-source...
Huipeng Ma, Luan Zhang, Dandan Song +10 more
In multi-hop reasoning, multi-round retrieval-augmented generation (RAG) methods typically rely on LLM-generated content as the retrieval query....
Weipeng Jiang, Xiaoyu Zhang, Juan Zhai +3 more
Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs) remain...
Shawn Li, Chenxiao Yu, Zhiyu Ni +4 more
Large language models (LLMs) are increasingly deployed in security-sensitive applications, where they must follow system- or developer-specified...
Mingxiang Tao, Yu Tian, Wenxuan Tu +3 more
Federated learning (FL) addresses data privacy and silo issues in large language models (LLMs). Most prior work focuses on improving the training...
Yixiao Peng, Hao Hu, Feiyang Li +5 more
While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand the...
Andrew D. Maynard
Large language model (LLM)-based conversational AI systems present a challenge to human cognition that current frameworks for understanding...
Hongyan Chang, Ergute Bao, Xinjian Luo +1 more
Large language models (LLMs) increasingly rely on retrieving information from external corpora. This creates a new attack surface: indirect prompt...
Harshil Parmar, Pushti Vyas, Prayers Khristi +1 more
As vulnerability research increasingly adopts generative AI, a critical reliance on opaque model outputs has emerged, creating a "trust gap" in...
Ying Zhou, Jiacheng Wei, Yu Qi +2 more
Large language models (LLMs) demonstrate remarkable capabilities in natural language understanding and generation. Despite being trained on...
Huihui Huang, Jieke Shi, Junkai Chen +6 more
Penetration testing is essential for identifying vulnerabilities in web applications before real adversaries can exploit them. Recent work has...
Masahiro Kaneko
The use of large language models (LLMs) in peer review systems has attracted growing attention, making it essential to examine their potential...
Takaaki Toda, Tatsuya Mori
Modern software package registries like PyPI have become critical infrastructure for software development, but are increasingly exploited by threat...
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