1 citations · 1 across the 9 of their papers we have counts for
11 papers
Federated Graph Retrieval-Augmented Generation
Xiaobao Wang, Renda Han, Zhiliang Xia +3
Graph Retrieval-Augmented Generation (GraphRAG) leverages centralized knowledge graphs to enhance large language models with structured knowledge retrieval. However, real-world kno…
Robust Graph Clustering Network for Multiple Missing Data
Keyuan Qiu, Renda Han, Zhen Tang +6
Clustering on graphs where both node attributes and structural links are partially missing remains a challenging task. Existing methods typically rely on imputation-then-clustering…
FlashSign: Pose-Free Guidance for Efficient Sign Language Video Generation
Liuzhou Zhang, Zeyu Zhang, Biao Wu +10
Sign language plays a crucial role in bridging communication gaps between the deaf and hard-of-hearing communities. However, existing sign language video generation models often re…
WebCryptoAgent: Agentic Crypto Trading with Web Informatics
Ali Kurban, Wei Luo, Liangyu Zuo +5
Cryptocurrency trading increasingly depends on timely integration of heterogeneous web information and market microstructure signals to support short-horizon decision making under…
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
Wenxin Zhang, Ding Xu, Guangzhen Yao +6
Time series anomaly detection is critical for system monitoring and risk identification, across various domains, such as finance and healthcare. However, for most reconstruction-ba…
Addressing Noise and Stochasticity in Fraud Detection for Service Networks
Wenxin Zhang, Ding Xu, Xi Xuan +5
Fraud detection is crucial in social service networks to maintain user trust and improve service network security. Existing spectral graph-based methods address this challenge by l…
DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly Detection
Wenxin Zhang, Xiaojian Lin, Wenjun Yu +7
Time series anomaly detection holds notable importance for risk identification and fault detection across diverse application domains. Unsupervised learning methods have become pop…
Dual-channel Heterophilic Message Passing for Graph Fraud Detection
Wenxin Zhang, Jingxing Zhong, Guangzhen Yao +4
Fraudulent activities have significantly increased across various domains, such as e-commerce, online review platforms, and social networks, making fraud detection a critical task.…
Dual Boost-Driven Graph-Level Clustering Network
John Smith, Wenxuan Tu, Junlong Wu +10
Graph-level clustering remains a pivotal yet formidable challenge in graph learning. Recently, the integration of deep learning with representation learning has demonstrated notabl…
MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction
Xuyin Qi, Zeyu Zhang, Huazhan Zheng +19
Bone density prediction via CT scans to estimate T-scores is crucial, providing a more precise assessment of bone health compared to traditional methods like X-ray bone density tes…
Multi-Relation Graph-Kernel Strengthen Network for Graph-Level Clustering
Renda Han, Guangzhen Yao, Wenxin Zhang +7
Graph-level clustering is a fundamental task of data mining, aiming at dividing unlabeled graphs into distinct groups. However, existing deep methods that are limited by pooling ha…