5 citations · 9 across the 5 of their papers we have counts for
5 papers
GraphFAS: A Distributed System for Automated Graph Feature Generation and Selection in Industrial Transaction Networks
Yice Luo, Yun Zhu, Xi Chen +7
Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relational signals, while GNNs often do not meet the interpretability and d…
AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelines
Xintan Zeng, Yongchao Liu, Yice Luo +1
Retrieval-Augmented Generation (RAG) enhances LLMs, but performance is highly sensitive to complex architecture designs and hyper-parameter configurations, which currently rely on…
GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs
Sheng Tian, Xintan Zeng, Yifei Hu +7
Graph-based patterns are extensively employed and favored by practitioners within industrial companies due to their capacity to represent the behavioral attributes and topological…
GIPA: General Information Propagation Algorithm for Graph Learning
Qinkai Zheng, Houyi Li, Peng Zhang +4
Graph neural networks (GNNs) have been popularly used in analyzing graph-structured data, showing promising results in various applications such as node classification, link predic…
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
Yongchao Liu, Houyi Li, Guowei Zhang +8
Graph neural networks (GNNs) have been demonstrated as a powerful tool for analyzing non-Euclidean graph data. However, the lack of efficient distributed graph learning systems sev…