2,077+ academic papers on AI security, attacks, and defenses
Showing 761–780 of 2,077 papers
Wenbo Guo, Shiwen Song, Jiaxun Guo +5 more
Open-source ecosystems such as NPM and PyPI are increasingly targeted by supply chain attacks, yet existing detection methods either depend on...
Khoa Nguyen, Khiem Ton, NhatHai Phan +6 more
Although boosting software development performance, large language model (LLM)-powered code generation introduces intellectual property and data...
Andres Karjus, Kais Allkivi, Silvia Maine +3 more
Large language models (LLMs) enable rapid and consistent automated evaluation of open-ended exam responses, including dimensions of content and...
Song Xia, Meiwen Ding, Chenqi Kong +2 more
Multimodal large language models (MLLMs) exhibit strong capabilities across diverse applications, yet remain vulnerable to adversarial perturbations...
Xiaoya Zheng, Geng Sun, Jiahui Li +5 more
The low-altitude economy (LAE) is an emerging economic paradigm which fosters integrated development across multiple fields. As a pivotal component...
Fengheng Chu, Jiahao Chen, Yuhong Wang +4 more
While Large Language Models (LLMs) are aligned to mitigate risks, their safety guardrails remain fragile against jailbreak attacks. This reveals...
Akriti Vij, Benjamin Chua, Darshini Ramiah +43 more
As frontier AI models are deployed globally, it is essential that their behaviour remains safe and reliable across diverse linguistic and cultural...
Mingyu Yu, Lana Liu, Zhehao Zhao +2 more
The rapid advancement of Multimodal Large Language Models (MLLMs) has introduced complex security challenges, particularly at the intersection of...
Kristen Moore, Diksha Goel, Cody James Christopher +5 more
Realistic network traffic simulation is critical for evaluating intrusion detection systems, stress-testing network protocols, and constructing...
Jiazhu Xie, Bowen Li, Heyu Fu +3 more
Large Language Model (LLM)-based question-answering systems offer significant potential for automating customer support and internal knowledge access...
Md Nabi Newaz Khan, Abdullah Arafat Miah, Yu Bi
Graph neural network (GNN) have demonstrated exceptional performance in solving critical problems across diverse domains yet remain susceptible to...
Sahar Tahmasebi, Eric Müller-Budack, Ralph Ewerth
Misinformation and fake news have become a pressing societal challenge, driving the need for reliable automated detection methods. Prior research has...
Piyumi Bhagya Sudasinghe, Kushan Sudheera Kalupahana Liyanage, Harsha S. Gardiyawasam Pussewalage
The rapid growth of Internet of Things (IoT) devices has increased the scale and diversity of cyberattacks, exposing limitations in traditional...
Anmol Goel, Cornelius Emde, Sangdoo Yun +2 more
We identify a novel phenomenon in language models: benign fine-tuning of frontier models can lead to privacy collapse. We find that diverse, subtle...
Xiaonan Jing, Gongqing Wu, Xingrui Zhuo +2 more
Open-domain Relational Triplet Extraction (ORTE) is the foundation for mining structured knowledge without predefined schemas. Despite the impressive...
Nilanjana Chatterjee, Sidharatha Garg, A V Subramanyam +1 more
Text-Based Person Search (TBPS) has seen significant progress with vision-language models (VLMs), yet it remains constrained by limited training data...
Keita Takeda, Tomoya Sakai
This study investigates the feature representations produced by publicly available open source medical vision-language models (VLMs). While medical...
Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim +6 more
Large language models (LLMs) are increasingly used as judges to evaluate agent performance, particularly in non-verifiable settings where judgments...
Zhihao Chen, Zirui Gong, Jianting Ning +2 more
Federated Rank Learning (FRL) is a promising Federated Learning (FL) paradigm designed to be resilient against model poisoning attacks due to its...
Yijin Zhou, Xiaoya Lu, Dongrui Liu +2 more
The rapid advancement of Large Language Model (LLM)-based Multi-Agent Systems (MAS) has introduced significant security vulnerabilities, where...
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