4 papers
MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning
Xukun Luan, Jinyan Liu, Yuhui Gong +4
Vision-Language models (VLMs) achieve outstanding performance largely due to the amount of training data available on the internet. At the same time, data holders (e.g., artists) u…
Code-Poisoning Property Inference Attacks
Xukun Luan, Yuhui Gong, Gang Zhang +4
The flourishing code hosting platforms and coding agents enable even beginners with private data to build tailored Machine Learning (ML) models using available code quickly. The tr…
VLALeaks: Membership Inference Attacks against Vision-Language-Action Models
Xukun Luan, Jinyan Liu, Xuesong Li +4
Vision-Language-Action (VLA) models enable end-to-end robot control and have garnered widespread attention. However, the memorization of training data inherent to VLA, coupled with…
FLAD: Federated Learning for LLM-based Autonomous Driving in Vehicle-Edge-Cloud Networks
Tianao Xiang, Mingjian Zhi, Yuanguo Bi +2
Large Language Models (LLMs) have impressive data fusion and reasoning capabilities for autonomous driving (AD). However, training LLMs for AD faces significant challenges includin…