2,077+ academic papers on AI security, attacks, and defenses
Showing 341–360 of 715 papers
Clear filtersHaoran Gu, Handing Wang, Yi Mei +2 more
The widespread deployment of large language models (LLMs) has raised growing concerns about their misuse risks and associated safety issues. While...
Manish Bhatt, Adrian Wood, Idan Habler +1 more
Production LLM agents with tool-using capabilities require security testing despite their safety training. We adapt Go-Explore to evaluate...
Ruben Neyroud, Sam Corley
While most LLMs are autoregressive, diffusion-based LLMs have recently emerged as an alternative method for generation. Greedy Coordinate Gradient...
Jingyu Zhang
Customer-service LLM agents increasingly make policy-bound decisions (refunds, rebooking, billing disputes), but the same ``helpful'' interaction...
Yuan Xin, Dingfan Chen, Linyi Yang +2 more
As large language models (LLMs) are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model...
Roee Ziv, Raz Lapid, Moshe Sipper
Audio-language models combine audio encoders with large language models to enable multimodal reasoning, but they also introduce new security...
Panagiotis Theocharopoulos, Ajinkya Kulkarni, Mathew Magimai. -Doss
Large language models (LLMs) are increasingly considered for use in high-impact workflows, including academic peer review. However, LLMs are...
Toqeer Ali Syed, Mishal Ateeq Almutairi, Mahmoud Abdel Moaty
Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models...
Toqeer Ali Syed, Mohammad Riyaz Belgaum, Salman Jan +2 more
The software supply chain attacks are becoming more and more focused on trusted development and delivery procedures, so the conventional post-build...
Manu, Yi Guo, Kanchana Thilakarathna +5 more
Large Language Models (LLMs) can be driven into over-generation, emitting thousands of tokens before producing an end-of-sequence (EOS) token. This...
Jiawei Liu, Zhuo Chen, Rui Zhu +4 more
Neural ranking models have achieved remarkable progress and are now widely deployed in real-world applications such as Retrieval-Augmented Generation...
Zhen Liang, Hai Huang, Zhengkui Chen
Large language models (LLMs), such as ChatGPT, have achieved remarkable success across a wide range of fields. However, their trustworthiness remains...
Soham Padia, Dhananjay Vaidya, Ramchandra Mangrulkar
Securing blockchain-enabled IoT networks against sophisticated adversarial attacks remains a critical challenge. This paper presents a trust-based...
Woorim 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...
Zongmin Zhang, Zhen Sun, Yifan Liao +5 more
Prompt-driven Video Segmentation Foundation Models (VSFMs) such as SAM2 are increasingly deployed in applications like autonomous driving and digital...
Chinmay Pushkar, Sanchit Kabra, Dhruv Kumar +1 more
Large Language Models (LLMs) have demonstrated significant potential in automated software security, particularly in vulnerability detection....
Mengqi He, Xinyu Tian, Xin Shen +4 more
Vision-language models (VLMs) achieve remarkable performance but remain vulnerable to adversarial attacks. Entropy, a measure of model uncertainty,...
Duo Chai, Zizhen Liu, Shuhuai Wang +4 more
Large language models (LLMs) are highly compute- and memory-intensive, posing significant demands on high-performance GPUs. At the same time,...
Tianwei Lan, Farid Naït-Abdesselam
The rapid growth in both the scale and complexity of Android malware has driven the widespread adoption of machine learning (ML) techniques for...
Xinjie Xu, Shuyu Cheng, Dongwei Xu +2 more
In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major...
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