2,529+ academic papers on AI security, attacks, and defenses
Showing 61–80 of 1,207 papers
Clear filtersZehui Tang, Yuchen Liu, Feihu Huang
Federated learning (FL) is a popular distributed learning paradigm in machine learning, which enables multiple clients to collaboratively train...
David Fernandez, Pedram MohajerAnsari, Amir Salarpour +1 more
Vision-language models (VLMs) are increasingly used in autonomous driving because they combine visual perception with language-based reasoning,...
Neha Nagaraja, Hayretdin Bahsi, Carlo R. da Cunha
As large language models are integrated into autonomous robotic systems for task planning and control, compromised inputs or unsafe model outputs can...
Mahshid Rezakhani, Nowfel Mashnoor, Kimia Azar +1 more
As large language models (LLMs) are increasingly fine-tuned for hardware tasks like RTL code generation, the scarcity of high-quality datasets often...
Wenhao Lan, Shan Li, Junbin Yang +2 more
Safety-aligned language models must refuse harmful requests without collapsing into broad over-refusal, but the training-time mechanisms behind this...
Zhijun Li, Minghui Xu, Huayi Qi +6 more
Retrieval-Augmented Generation (RAG) is essential for enhancing Large Language Models (LLMs) with external knowledge, but its reliance on cloud...
Zhijun Li, Minghui Xu, Huayi Qi +6 more
Retrieval-Augmented Generation (RAG) is essential for enhancing Large Language Models (LLMs) with external knowledge, but its reliance on cloud...
Yuan Xin, Yixuan Weng, Minjun Zhu +6 more
As Large Language Models (LLMs) are increasingly integrated into academic peer review, their vulnerability to adversarial prompts -- adversarial...
Hanna Foerster, Ilia Shumailov, Cheng Zhang +3 more
Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static...
Kemal Bicakci
Public agencies are beginning to consider large language models (LLMs) as decision-support tools for grant evaluation. This creates a practical...
Runze Cui, Fangxin Shang, Yehui Yang +2 more
Document understanding is a critical capability in financial credit review, onboarding, and remote verification, where both decision accuracy and...
Yuanfan Li, Qi Zhou, Chengzhengxu Li +5 more
We present MGTEVAL, an extensible platform for systematic evaluation of Machine-Generated Text (MGT) detectors. Despite rapid progress in MGT...
Ravikumar Balakrishnan, Sanket Mendapara
Typographic prompt injection exploits vision language models' (VLMs) ability to read text rendered in images, posing a growing threat as VLMs power...
Xiaohang Yu, Hejia Geng, William Knottenbelt
Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's bearer-secret interfaces implement...
Aaron J. Li, Nicolas Sanchez, Hao Huang +8 more
Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users...
Qi Li, Jiu Li, Pingtao Wei +8 more
This report presents a comparative evaluation of DKnownAI Guard in AI agent security scenarios, benchmarked against three competing products: AWS...
Nay Myat Min, Long H. Pham, Jun Sun
Large language models deployed at runtime can misbehave in ways that clean-data validation cannot anticipate: training-time backdoors lie dormant...
Pablo Mateo-Torrejón, Alfonso Sánchez-Macián
The rapid integration of Large Language Models (LLMs) into Multi-Agent Systems (MAS) has significantly enhanced their collaborative problem-solving...
Zihan Liu, Yizhen Wang, Rui Wang +2 more
Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for...
Mengnan Zhao, Lihe Zhang, Tianhang Zheng +2 more
Fast Adversarial Training (FAT) has attracted significant attention due to its efficiency in enhancing neural network robustness against adversarial...
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