2,077+ academic papers on AI security, attacks, and defenses
Showing 961–978 of 978 papers
Clear filtersZeyu Shen, Basileal Imana, Tong Wu +3 more
Retrieval-Augmented Generation (RAG) enhances Large Language Models by grounding their outputs in external documents. These systems, however, remain...
Charles E. Gagnon, Steven H. H. Ding, Philippe Charland +1 more
Binary code similarity detection is a core task in reverse engineering. It supports malware analysis and vulnerability discovery by identifying...
Han Yan, Zheyuan Liu, Meng Jiang
With the rapid advancement of large language models, Machine Unlearning has emerged to address growing concerns around user privacy, copyright...
Xiaotian Zou
Multimodal Large Language Models (MLLMs) have transformed text-to-image workflows, allowing designers to create novel visual concepts with...
Jeongyeon Hwang, Sangdon Park, Jungseul Ok
Watermarking offers a promising solution for detecting LLM-generated content, yet its robustness under realistic query-free (black-box) evasion...
Xingyu Li, Juefei Pu, Yifan Wu +13 more
Open-source software projects are foundational to modern software ecosystems, with the Linux kernel standing out as a critical exemplar due to its...
Antreas Ioannou, Andreas Shiamishis, Nora Hollenstein +1 more
In an era dominated by Large Language Models (LLMs), understanding their capabilities and limitations, especially in high-stakes fields like law, is...
Nakyeong Yang, Dong-Kyum Kim, Jea Kwon +3 more
Large language models trained on web-scale data can memorize private or sensitive knowledge, raising significant privacy risks. Although some...
Haochen Gong, Chenxiao Li, Rui Chang +1 more
Large language model (LLM)-based computer-use agents represent a convergence of AI and OS capabilities, enabling natural language to control system-...
Jiayu Ding, Xinpeng Liu, Zhiyi Pan +2 more
Lifting 2D open-vocabulary understanding into 3D Gaussian Splatting (3DGS) scenes is a critical challenge. However, mainstream methods suffer from...
Lukas Twist, Jie M. Zhang, Mark Harman +1 more
Large language models (LLMs) are increasingly used to generate code, yet they continue to hallucinate, often inventing non-existent libraries. Such...
David Benfield, Stefano Coniglio, Phan Tu Vuong +1 more
Adversarial machine learning concerns situations in which learners face attacks from active adversaries. Such scenarios arise in applications such as...
Anton Korznikov, Andrey Galichin, Alexey Dontsov +3 more
Activation steering is a promising technique for controlling LLM behavior by adding semantically meaningful vectors directly into a model's hidden...
Bochuan Cao, Changjiang Li, Yuanpu Cao +3 more
Large language models (LLMs) have been widely adopted across various applications, leveraging customized system prompts for diverse tasks. Facing...
Jaehan Kim, Minkyoo Song, Seungwon Shin +1 more
Recent large language models (LLMs) have increasingly adopted the Mixture-of-Experts (MoE) architecture for efficiency. MoE-based LLMs heavily depend...
Daiki Chiba, Hiroki Nakano, Takashi Koide
Phishing attacks are a significant societal threat, disproportionately harming vulnerable populations and eroding trust in essential digital...
Miao Yu, Zhenhong Zhou, Moayad Aloqaily +5 more
Fine-tuned Large Language Models (LLMs) are vulnerable to backdoor attacks through data poisoning, yet the internal mechanisms governing these...
Prakhar Sharma, Haohuang Wen, Vinod Yegneswaran +3 more
The evolution toward 6G networks is being accelerated by the Open Radio Access Network (O-RAN) paradigm -- an open, interoperable architecture that...
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