6 papers
FAgent: Financial Fusion of Agentic Intelligence for Multimodal Trading
Changshuo Liu, Yanzheng Jin, Shangfeng Cai +3
With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial trading. Although recent adva…
Differentially Private Contrastive Learning via Bounding Group-level Contribution
Kecen Li, Chen Gong, Zinan Lin +2
Differentially private (DP) contrastive learning aims to learn general-purpose representations from sensitive data, alleviating the privacy leakage concerns of organizations deploy…
NeurStore: Efficient In-database Deep Learning Model Management System
Siqi Xiang, Sheng Wang, Xiaokui Xiao +3
With the prevalence of in-database AI-powered analytics, there is an increasing demand for database systems to efficiently manage the ever-expanding number and size of deep learnin…
Prompt Inference Attack on Distributed Large Language Model Inference Frameworks
Xinjian Luo, Ting Yu, Xiaokui Xiao
The inference process of modern large language models (LLMs) demands prohibitive computational resources, rendering them infeasible for deployment on consumer-grade devices. To add…
Passive Inference Attacks on Split Learning via Adversarial Regularization
Xiaochen Zhu, Xinjian Luo, Yuncheng Wu +3
Split Learning (SL) has emerged as a practical and efficient alternative to traditional federated learning. While previous attempts to attack SL have often relied on overly strong…
GCON: Differentially Private Graph Convolutional Network via Objective Perturbation
Jianxin Wei, Yizheng Zhu, Xiaokui Xiao +4
Graph Convolutional Networks (GCNs) are a popular machine learning model with a wide range of applications in graph analytics, including healthcare, transportation, and finance. Ho…