2,077+ academic papers on AI security, attacks, and defenses
Showing 1841–1860 of 2,048 papers
Clear filtersXiangtao Meng, Tianshuo Cong, Li Wang +4 more
Large Language Models (LLMs) have shown remarkable performance across various applications, but their deployment in real-world settings faces several...
Weisen Jiang, Sinno Jialin Pan
This paper introduces MetaDefense, a novel framework for defending against finetuning-based jailbreak attacks in large language models (LLMs). We...
Eric Hanchen Jiang, Weixuan Ou, Run Liu +8 more
Safety alignment of large language models currently faces a central challenge: existing alignment techniques often prioritize mitigating responses to...
Renhua Ding, Xiao Yang, Zhengwei Fang +3 more
Large vision-language models (LVLMs) enable autonomous mobile agents to operate smartphone user interfaces, yet vulnerabilities in their perception...
Man Hu, Xinyi Wu, Zuofeng Suo +5 more
With the rise of advanced reasoning capabilities, large language models (LLMs) are receiving increasing attention. However, although reasoning...
Chongyu Fan, Changsheng Wang, Yancheng Huang +2 more
Machine unlearning for large language models (LLMs) aims to remove undesired data, knowledge, and behaviors (e.g., for safety, privacy, or copyright)...
Rupam Patir, Keyan Guo, Haipeng Cai +1 more
The code generation capabilities of Large Language Models (LLMs) have transformed the field of software development. However, this advancement also...
Shen Dong, Mingxuan Zhang, Pengfei He +4 more
Large Language Model (LLM)-based Multi-Agent Systems (MAS) have emerged as a powerful paradigm for tackling complex, multi-step tasks across diverse...
Christos Ziakas, Nicholas Loo, Nishita Jain +1 more
Automated red-teaming has emerged as a scalable approach for auditing Large Language Models (LLMs) prior to deployment, yet existing approaches lack...
Abhishek Anand, Matthias C. Caro, Ari Karchmer +1 more
Quantum learning from remotely accessed quantum compute and data must address two key challenges: verifying the correctness of data and ensuring the...
Junjie Li, Fazle Rabbi, Bo Yang +2 more
Although Large Language Models (LLMs) show promising solutions to automated code generation, they often produce insecure code that threatens software...
Artur Horal, Daniel Pina, Henrique Paz +7 more
This paper presents the vision, scientific contributions, and technical details of RedTWIZ: an adaptive and diverse multi-turn red teaming framework,...
Muris Sladić, Veronica Valeros, Carlos Catania +1 more
There are very few SotA deception systems based on Large Language Models. The existing ones are limited only to simulating one type of service,...
Riku Mochizuki, Shusuke Komatsu, Souta Noguchi +1 more
We analyze answers generated by generative engines (GEs) from the perspectives of citation publishers and the content-injection barrier, defined as...
Tavish McDonald, Bo Lei, Stanislav Fort +2 more
Models are susceptible to adversarially out-of-distribution (OOD) data despite large training-compute investments into their robustification. Zaremba...
Tiancheng Xing, Jerry Li, Yixuan Du +1 more
Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small,...
Zhiyuan Wei, Xiaoxuan Yang, Jing Sun +1 more
The increasing complexity of modern software systems exacerbates the prevalence of security vulnerabilities, posing risks of severe breaches and...
Weidi Luo, Qiming Zhang, Tianyu Lu +9 more
Computer-use agent (CUA) frameworks, powered by large language models (LLMs) or multimodal LLMs (MLLMs), are rapidly maturing as assistants that can...
Sri Durga Sai Sowmya Kadali, Evangelos E. Papalexakis
Jailbreaking large language models (LLMs) has emerged as a pressing concern with the increasing prevalence and accessibility of conversational LLMs....
Thusitha Dayaratne, Ngoc Duy Pham, Viet Vo +5 more
The quality and experience of mobile communication have significantly improved with the introduction of 5G, and these improvements are expected to...
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