2,077+ academic papers on AI security, attacks, and defenses
Showing 441–460 of 986 papers
Clear filtersAndreea-Elena Bodea, Stephen Meisenbacher, Alexandra Klymenko +1 more
The continued promise of Large Language Models (LLMs), particularly in their natural language understanding and generation capabilities, has driven a...
Xiaoyu Xu, Minxin Du, Zitong Li +6 more
Although machine unlearning is essential for removing private, harmful, or copyrighted content from LLMs, current benchmarks often fail to faithfully...
Xing Li, Hui-Ling Zhen, Lihao Yin +3 more
This paper presents a comprehensive empirical study on the safety alignment capabilities. We evaluate what matters for safety alignment in LLMs and...
Dinesh Srivasthav P, Ashok Urlana, Rahul Mishra +2 more
Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Right to...
Di Wu, Yanyan Zhao, Xin Lu +2 more
Defending against jailbreak attacks is crucial for the safe deployment of Large Language Models (LLMs). Recent research has attempted to improve...
Sofie Goethals, Foster Provost, João Sedoc
As generative AI systems become integrated into real-world applications, organizations increasingly need to be able to understand and interpret their...
Bocheng Chen, Xi Chen, Han Zi +5 more
Identifying specific moral errors in an input and generating appropriate corrections require moral sensitivity in large language models (LLMs), which...
Gaurav Sarraf, Vibhor Pal
Cloud computing has changed online communities in three dimensions, which are scalability, adaptability and reduced overhead. But there are serious...
Ahmed Ahmed, A. Feder Cooper, Sanmi Koyejo +1 more
Many unresolved legal questions over LLMs and copyright center on memorization: whether specific training data have been encoded in the model's...
Md Ajoad Hasan, Dipayan Saha, Khan Thamid Hasan +5 more
The growing complexity of modern system-on-chip (SoC) and IP designs is making security assurance difficult day by day. One of the fundamental steps...
Neusha Javidnia, Ruisi Zhang, Ashish Kundu +1 more
We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLM owners by...
Maryam Abbasihafshejani, AHM Nazmus Sakib, Murtuza Jadliwala
The rapid advancement of speech synthesis technologies, including text-to-speech (TTS) and voice conversion (VC), has intensified security and...
Antonio Colacicco, Vito Guida, Dario Di Palma +2 more
Large Language Models (LLMs) are increasingly applied in recommendation scenarios due to their strong natural language understanding and generation...
Jiwei Guan, Haibo Jin, Haohan Wang
Recent advancements in Large Vision-Language Models (LVLMs) have shown groundbreaking capabilities across diverse multimodal tasks. However, these...
Jinwei Hu, Xinmiao Huang, Youcheng Sun +2 more
As large language models (LLMs) transition to autonomous agents synthesizing real-time information, their reasoning capabilities introduce an...
Arina Kharlamova, Youcheng Sun, Ting Yu
Private macOS frameworks underpin critical services and daemons but remain undocumented and distributed only as stripped binaries, complicating...
Junyu Liu, Zirui Li, Qian Niu +7 more
As Large Language Models (LLMs) are increasingly deployed in healthcare field, it becomes essential to carefully evaluate their medical safety before...
Huan Lin Oh, Jay Yong Jun Jie, Mandy Lee Ling Siu +1 more
Cybersecurity post-incident reviews are essential for identifying control failures and improving organisational resilience, yet they remain...
Muntasir Adnan, Carlos C. N. Kuhn
Large Language Models have become integral to software development, yet they frequently generate vulnerable code. Existing code vulnerability...
Davis Brown, Juan-Pablo Rivera, Dan Hendrycks +1 more
As frontier AIs become more powerful and costly to develop, adversaries have increasing incentives to steal model weights by mounting exfiltration...
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