2,077+ academic papers on AI security, attacks, and defenses
Showing 1441–1460 of 2,077 papers
Ruoxi Cheng, Haoxuan Ma, Teng Ma +1 more
Large Vision-Language Models (LVLMs) exhibit powerful reasoning capabilities but suffer sophisticated jailbreak vulnerabilities. Fundamentally,...
Biagio Boi, Christian Esposito
Smart contracts have emerged as key components within decentralized environments, enabling the automation of transactions through self-executing...
Farhad Abtahi, Fernando Seoane, Iván Pau +1 more
Healthcare AI systems face major vulnerabilities to data poisoning that current defenses and regulations cannot adequately address. We analyzed eight...
Zichao Wei, Jun Zeng, Ming Wen +8 more
Software vulnerabilities are increasing at an alarming rate. However, manual patching is both time-consuming and resource-intensive, while existing...
Feilong Wang, Fuqiang Liu
The integration of large language models (LLMs) into automated driving systems has opened new possibilities for reasoning and decision-making by...
Guangke Chen, Yuhui Wang, Shouling Ji +2 more
Modern text-to-speech (TTS) systems, particularly those built on Large Audio-Language Models (LALMs), generate high-fidelity speech that faithfully...
Dennis Wei, Ronny Luss, Xiaomeng Hu +6 more
Large Language Models (LLMs) have become ubiquitous in everyday life and are entering higher-stakes applications ranging from summarizing meeting...
Fred Heiding, Simon Lermen
We present an end-to-end demonstration of how attackers can exploit AI safety failures to harm vulnerable populations: from jailbreaking LLMs to...
Runpeng Geng, Yanting Wang, Chenlong Yin +3 more
Long context LLMs are vulnerable to prompt injection, where an attacker can inject an instruction in a long context to induce an LLM to generate an...
Srikant Panda, Avinash Rai
Large Language Models (LLMs) are commonly evaluated for robustness against paraphrased or semantically equivalent jailbreak prompts, yet little...
Shuaitong Liu, Renjue Li, Lijia Yu +3 more
Recent advances in Chain-of-Thought (CoT) prompting have substantially improved the reasoning capabilities of large language models (LLMs), but have...
Yuping Yan, Yuhan Xie, Yuanshuai Li +3 more
Since Multimodal Large Language Models (MLLMs) are increasingly being integrated into everyday tools and intelligent agents, growing concerns have...
Yudong Yang, Xuezhen Zhang, Zhifeng Han +6 more
Recent progress in LLMs has enabled understanding of audio signals, but has also exposed new safety risks arising from complex audio inputs that are...
Zihan Wang, Guansong Pang, Wenjun Miao +2 more
Recent advances in Large Visual Language Models (LVLMs) have demonstrated impressive performance across various vision-language tasks by leveraging...
Francis Rhys Ward, Teun van der Weij, Hanna Gábor +6 more
AI systems are increasingly able to autonomously conduct realistic software engineering tasks, and may soon be deployed to automate machine learning...
Jialin Wu, Kecen Li, Zhicong Huang +3 more
Many machine learning models are fine-tuned from large language models (LLMs) to achieve high performance in specialized domains like code...
Catherine Xia, Manar H. Alalfi
AI programming assistants have demonstrated a tendency to generate code containing basic security vulnerabilities. While developers are ultimately...
James Jin Kang, Dang Bui, Thanh Pham +1 more
The growing use of large language models in sensitive domains has exposed a critical weakness: the inability to ensure that private information can...
Gabrielle M Gauthier, Eesha Ali, Amna Asim +2 more
Human content moderators (CMs) routinely review distressing digital content at scale. Beyond exposure, the work context (e.g., workload, team...
Yuankai He, Weisong Shi
CAR-Scenes is a frame-level dataset for autonomous driving that enables training and evaluation of vision-language models (VLMs) for interpretable,...
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