2,077+ academic papers on AI security, attacks, and defenses
Showing 41–60 of 79 papers
Clear filtersWoorim Han, Yeongjun Kwak, Miseon Yu +4 more
Learning-based automated vulnerability repair (AVR) techniques that utilize fine-tuned language models have shown promise in generating vulnerability...
Chinmay Pushkar, Sanchit Kabra, Dhruv Kumar +1 more
Large Language Models (LLMs) have demonstrated significant potential in automated software security, particularly in vulnerability detection....
Zhenlei Ye, Xiaobing Sun, Sicong Cao +2 more
The advances of large language models (LLMs) have paved the way for automated software vulnerability repair approaches, which iteratively refine the...
Liming Lu, Xiang Gu, Junyu Huang +5 more
Large Language Models (LLMs) are increasingly used in agentic systems, where their interactions with diverse tools and environments create complex,...
Zhang Wei, Peilu Hu, Zhenyuan Wei +16 more
The increasing deployment of large language models (LLMs) in safety-critical applications raises fundamental challenges in systematically evaluating...
Safwan Shaheer, G. M. Refatul Islam, Mohammad Rafid Hamid +1 more
In this fast-evolving area of LLMs, our paper discusses the significant security risk presented by prompt injection attacks. It focuses on small...
Chaomeng Lu, Bert Lagaisse
Vulnerability detection methods based on deep learning (DL) have shown strong performance on benchmark datasets, yet their real-world effectiveness...
Devanshu Sahoo, Vasudev Majhi, Arjun Neekhra +3 more
The use of Large Language Models (LLMs) as automatic judges for code evaluation is becoming increasingly prevalent in academic environments. But...
Futa Waseda, Shojiro Yamabe, Daiki Shiono +2 more
Large vision-language models (LVLMs) are vulnerable to typographic attacks, where misleading text within an image overrides visual understanding....
Xiaojun Jia, Jie Liao, Qi Guo +11 more
Recent advances in multi-modal large language models (MLLMs) have enabled unified perception-reasoning capabilities, yet these systems remain highly...
Caleb Gross
Security research is fundamentally a problem of resource constraint and consequent prioritization. There is simply too much attack surface and too...
Xiuyuan Chen, Jian Zhao, Yuxiang He +10 more
While the deployment of large language models (LLMs) in high-value industries continues to expand, the systematic assessment of their safety against...
Songwen Zhao, Danqing Wang, Kexun Zhang +3 more
Vibe coding is a new programming paradigm in which human engineers instruct large language model (LLM) agents to complete complex coding tasks with...
Jiawei Chen, Yang Yang, Chao Yu +6 more
Large Reasoning Models (LRMs) have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical...
Juncheng Li, Yige Li, Hanxun Huang +5 more
Backdoor attacks undermine the reliability and trustworthiness of machine learning systems by injecting hidden behaviors that can be maliciously...
Zhijie Chen, Xiang Chen, Ziming Li +2 more
Context: Software Vulnerability Assessment (SVA) plays a vital role in evaluating and ranking vulnerabilities in software systems to ensure their...
Chunyang Li, Zifeng Kang, Junwei Zhang +4 more
The adoption of Vision-Language Models (VLMs) in embodied AI agents, while being effective, brings safety concerns such as jailbreaking. Prior work...
Henry Wong, Clement Fung, Weiran Lin +3 more
To autonomously control vehicles, driving agents use outputs from a combination of machine-learning (ML) models, controller logic, and custom...
Jiayu Li, Yunhan Zhao, Xiang Zheng +4 more
Vision-Language-Action (VLA) models enable robots to interpret natural-language instructions and perform diverse tasks, yet their integration of...
Zhishen Sun, Guang Dai, Haishan Ye
LLMs demonstrate performance comparable to human abilities in complex tasks such as mathematical reasoning, but their robustness in mathematical...
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