2,529+ academic papers on AI security, attacks, and defenses
Showing 1901–1909 of 1,909 papers
Clear filtersRunpeng 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...
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