7 accepted papers
Online time series forecasting relies on continual updates to cope with concept drift. In multi-step forecasting, however, the ground truth for an H-step prediction arrives only after H steps, so a delayed residual entangles persistent drifts with transient shocks and seasonal fluctuations. Existing
Pre-trained language models (PLMs) have shown strong potential in Ethereum account modeling and fraud detection. However, existing approaches often overlook the graph-structured nature of transaction networks. In addition, they struggle with the long-tail distribution of account activity, resulting
Split inference (SI) enables users to access deep learning (DL) services without directly transmitting raw data. However, recent studies reveal that data reconstruction attacks (DRAs) can recover the original inputs from the smashed data sent from the client to the server, leading to significant pri
Despite the remarkable progress of Large Language Model (LLM) based Multi-Agent Systems, most research focuses on optimizing coordination topology while largely underexploring the equally critical problem: how to transmit and optimize messages among agents effectively? Current communication schemes …
Hidden degenerations in industrial time series often precede observable failures, they remain undetected by standard monitoring systems until anomalies become apparent. This gap between microscopic degradation and macroscopic observation renders conventional predictors inherently reactive, as they r
Federated Graph Neural Network (FedGNN) integrate federated learning (FL) with graph neural networks (GNNs) to enable privacy-preserving training on distributed graph data. Vertical Federated Graph Neural Network (VFGNN), a key branch of FedGNN, handles scenarios where data features and labels are d
Backdoor attacks in vertical federated learning (VFL) are particularly concerning as they can covertly compromise VFL decision-making, posing a severe threat to critical applications of VFL. Existing defense mechanisms typically involve either label obfuscation during training or model pruning durin