2,077+ academic papers on AI security, attacks, and defenses
Showing 261–280 of 2,077 papers
Byung-Kwan Lee, Youngchae Chee, Yong Man Ro
Think-Answer reasoners such as DeepSeek-R1 have made notable progress by leveraging interpretable internal reasoning. However, despite the frequent...
Huw Day, Adrianna Jezierska, Jessica Woodgate
Large Language Models have intensified the scale and strategic manipulation of political discourse on social media, leading to conflict escalation....
Guoxin Shi, Haoyu Wang, Zaihui Yang +2 more
Adversarial behavior plays a central role in aligning large language models with human values. However, existing alignment methods largely rely on...
Rong Fu, Yiqing Lyu, Chunlei Meng +9 more
Automatic generation of radiology reports seeks to reduce clinician workload while improving documentation consistency. Existing methods that adopt...
Xiangyang Zhu, Yuan Tian, Qi Jia +14 more
The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their...
Xiaoyi Pang, Xuanyi Hao, Pengyu Liu +3 more
Recent intelligent systems integrate powerful Large Language Models (LLMs) through APIs, but their trustworthiness may be critically undermined by...
Zhihang Deng, Jiaping Gui, Weinan Zhang
Large Language Models (LLMs) are increasingly deployed as agentic systems that plan, memorize, and act in open-world environments. This shift brings...
Yu Lin, Qizhi Zhang, Wenqiang Ruan +6 more
The rapid development of large language models (LLMs) has driven the widespread adoption of cloud-based LLM inference services, while also bringing...
Manisha Mukherjee, Vincent J. Hellendoorn
Large Language Models (LLMs) are increasingly deployed for code generation in high-stakes software development, yet their limited transparency in...
Duoxun Tang, Dasen Dai, Jiyao Wang +3 more
Video-LLMs are increasingly deployed in safety-critical applications but are vulnerable to Energy-Latency Attacks (ELAs) that exhaust computational...
Xinyu Huang, Qiang Yang, Leming Shen +2 more
Embodied Large Language Models (LLMs) enable AI agents to interact with the physical world through natural language instructions and actions....
Rahul Marchand, Art O Cathain, Jerome Wynne +5 more
Large language models (LLMs) increasingly act as autonomous agents, using tools to execute code, read and write files, and access networks, creating...
Masahiro Kaneko, Ayana Niwa, Timothy Baldwin
Fake news undermines societal trust and decision-making across politics, economics, health, and international relations, and in extreme cases...
Haochen Liang, Jiawei Chen, Hideya Ochiai
Hybrid fuzzing combines greybox fuzzing's throughput with the precision of symbolic execution to uncover deep smart contract vulnerabilities....
Qingxiao Xu, Ze Sheng, Zhicheng Chen +1 more
Large language models (LLMs) have shown promise for automated patching, but their effectiveness depends strongly on how they are integrated into...
Mingcheng Jiang, Jiancheng Huang, Jiangfei Wang +5 more
Static Application Security Testing (SAST) tools often suffer from high false positive rates, leading to alert fatigue that consumes valuable...
Huajie Chen, Tianqing Zhu, Yuchen Zhong +7 more
Dataset distillation compresses a large real dataset into a small synthetic one, enabling models trained on the synthetic data to achieve performance...
Jiayao Wang, Yiping Zhang, Mohammad Maruf Hasan +5 more
Self-supervised diffusion models learn high-quality visual representations via latent space denoising. However, their representation layer poses a...
Martin Odersky, Yaoyu Zhao, Yichen Xu +2 more
AI agents that interact with the real world through tool calls pose fundamental safety challenges: agents might leak private information, cause...
Oluseyi Olukola, Nick Rahimi
Machine learning based network intrusion detection systems are vulnerable to adversarial attacks that degrade classification performance under both...
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