2,560+ academic papers on AI security, attacks, and defenses
Showing 561–580 of 728 papers
Clear filtersYuan Xin, Dingfan Chen, Linyi Yang +2 more
As large language models (LLMs) are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model...
Ruixuan Huang, Qingyue Wang, Hantao Huang +4 more
Mixture-of-Experts architectures have become the standard for scaling large language models due to their superior parameter efficiency. To...
Roee Ziv, Raz Lapid, Moshe Sipper
Audio-language models combine audio encoders with large language models to enable multimodal reasoning, but they also introduce new security...
Jiawei Liu, Zhuo Chen, Rui Zhu +4 more
Neural ranking models have achieved remarkable progress and are now widely deployed in real-world applications such as Retrieval-Augmented Generation...
Zhen Liang, Hai Huang, Zhengkui Chen
Large language models (LLMs), such as ChatGPT, have achieved remarkable success across a wide range of fields. However, their trustworthiness remains...
Soham Padia, Dhananjay Vaidya, Ramchandra Mangrulkar
Securing blockchain-enabled IoT networks against sophisticated adversarial attacks remains a critical challenge. This paper presents a trust-based...
Zongmin Zhang, Zhen Sun, Yifan Liao +5 more
Prompt-driven Video Segmentation Foundation Models (VSFMs) such as SAM2 are increasingly deployed in applications like autonomous driving and digital...
Jiayu Hu, Beibei Li, Jiangwei Xia +3 more
While Vision-Language Models (VLMs) have garnered increasing attention in the AI community due to their promising practical applications, they...
Mengqi He, Xinyu Tian, Xin Shen +4 more
Vision-language models (VLMs) achieve remarkable performance but remain vulnerable to adversarial attacks. Entropy, a measure of model uncertainty,...
Tsogt-Ochir Enkhbayar
Warning-framed content in training data (e.g., "DO NOT USE - this code is vulnerable") does not, it turns out, teach language models to avoid the...
Tian Li, Bo Lin, Shangwen Wang +1 more
Retrieval-Augmented Code Generation (RACG) is increasingly adopted to enhance Large Language Models for software development, yet its security...
Duo Chai, Zizhen Liu, Shuhuai Wang +4 more
Large language models (LLMs) are highly compute- and memory-intensive, posing significant demands on high-performance GPUs. At the same time,...
Tianwei Lan, Farid Naït-Abdesselam
The rapid growth in both the scale and complexity of Android malware has driven the widespread adoption of machine learning (ML) techniques for...
Haoyang Li, Mingjin Li, Jinxin Zuo +5 more
LLM-based code agents(e.g., ChatGPT Codex) are increasingly deployed as detector for code review and security auditing tasks. Although CoT-enhanced...
Xinjie Xu, Shuyu Cheng, Dongwei Xu +2 more
In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major...
Ahmed M. Hussain, Salahuddin Salahuddin, Panos Papadimitratos
Current Large Language Models (LLMs) safety approaches focus on explicitly harmful content while overlooking a critical vulnerability: the inability...
Lichao Wu, Sasha Behrouzi, Mohamadreza Rostami +2 more
Mixture-of-Experts (MoE) architectures have advanced the scaling of Large Language Models (LLMs) by activating only a sparse subset of parameters per...
Yihan Wang, Huanqi Yang, Shantanu Pal +1 more
The integration of Large Language Models (LLMs) into wearable sensing is creating a new class of mobile applications capable of nuanced human...
Yifan Yao, Baojuan Wang, Jinhao Duan +4 more
Chat-based cybercrime has emerged as a pervasive threat, with attackers leveraging real-time messaging platforms to conduct scams that rely on...
Omer Gazit, Yael Itzhakev, Yuval Elovici +1 more
Radio frequency (RF) based systems are increasingly used to detect drones by analyzing their RF signal patterns, converting them into spectrogram...
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