2,529+ academic papers on AI security, attacks, and defenses
Showing 581–600 of 729 papers
Clear filtersZishuo Zheng, Vidhisha Balachandran, Chan Young Park +2 more
As large language model (LLM) based systems take on high-stakes roles in real-world decision-making, they must reconcile competing instructions from...
Aylton Almeida, Laerte Xavier, Marco Tulio Valente
Keeping software systems up to date is essential to avoid technical debt, security vulnerabilities, and the rigidity typical of legacy systems....
Shaked Zychlinski, Yuval Kainan
Large Language Models (LLMs) are susceptible to jailbreak attacks where malicious prompts are disguised using ciphers and character-level encodings...
Yingjia Wang, Ting Qiao, Xing Liu +3 more
The rapid advancement of deep neural networks (DNNs) heavily relies on large-scale, high-quality datasets. However, unauthorized commercial use of...
Zheng Zhang, Haonan Li, Xingyu Li +2 more
Bug bisection has been an important security task that aims to understand the range of software versions impacted by a bug, i.e., identifying the...
Kaiwen Zhou, Ahmed Elgohary, A S M Iftekhar +1 more
The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for...
André V. Duarte, Xuying li, Bin Zeng +3 more
If we cannot inspect the training data of a large language model (LLM), how can we ever know what it has seen? We believe the most compelling...
Emily Herron, Junqi Yin, Feiyi Wang
Large language models (LLMs) have demonstrated transformative potential in scientific research, yet their deployment in high-stakes contexts raises...
Simon Yu, Peilin Yu, Hongbo Zheng +3 more
We present VISAT, a novel open dataset and benchmarking suite for evaluating model robustness in the task of traffic sign recognition with the...
He Hu, Chiyuan Ma, Qianning Wang +5 more
The shortage of mental health professionals has driven the web to become a primary avenue for accessible psychological support. While Large Language...
Zheng Zhang, Guanlong Wu, Sen Deng +2 more
In the rapidly expanding landscape of Large Language Model (LLM) applications, real-time output streaming has become the dominant interaction...
Juan Ren, Mark Dras, Usman Naseem
Agentic methods have emerged as a powerful and autonomous paradigm that enhances reasoning, collaboration, and adaptive control, enabling systems to...
Yifan Wu, Xuewei Feng, Yuxiang Yang +1 more
As the core of the Internet infrastructure, the TCP/IP protocol stack undertakes the task of network data transmission. However, due to the...
María Sanz-Gómez, Víctor Mayoral-Vilches, Francesco Balassone +3 more
Cybersecurity spans multiple interconnected domains, complicating the development of meaningful, labor-relevant benchmarks. Existing benchmarks...
Vladyslav Larin, Ihor Naumenko, Aleksei Ivashov +2 more
As centralized AI hits compute ceilings and diminishing returns from ever-larger training runs, meeting demand requires an inference layer that...
Hiromu Takahashi, Shotaro Ishihara
We propose Fast-MIA (https://github.com/Nikkei/fast-mia), a Python library for efficiently evaluating membership inference attacks (MIA) against...
Armin Gerami, Kazem Faghih, Ramani Duraiswami
Retrieval Augmented Generation (RAG) enhances Large Language Models (LLMs) by connecting them to external knowledge, improving accuracy and reducing...
Julia Bazinska, Max Mathys, Francesco Casucci +4 more
AI agents powered by large language models (LLMs) are being deployed at scale, yet we lack a systematic understanding of how the choice of backbone...
Hao Zheng, Zirui Pang, Ling li +5 more
Advances in Multimodal Large Language Models (MLLMs) intensify concerns about data privacy, making Machine Unlearning (MU), the selective removal of...
Wenxuan Bao, Ruxi Deng, Jingrui He
Pretrained vision-language models such as CLIP achieve strong zero-shot generalization but remain vulnerable to distribution shifts caused by input...
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