5 papers
Robust Multimodal Recommendation via Graph Retrieval-Enhanced Modality Completion
Yuan Li, Jun Hu, Jiaxin Jiang +2
Multimodal data plays a critical role in web-based recommendation systems, where information from diverse modalities such as vision and text enhances representation learning. Howev…
Efficient Densest Flow Queries in Transaction Flow Networks (Complete Version)
Jiaxin Jiang, Yunxiang Zhao, Lyu Xu +4
Transaction flow networks are crucial in detecting illicit activities such as wash trading, credit card fraud, cashback arbitrage fraud, and money laundering. \revise{Our collabora…
Dupin: A Parallel Framework for Densest Subgraph Discovery in Fraud Detection on Massive Graphs (Technical Report)
Jiaxin Jiang, Siyuan Yao, Yuchen Li +3
Detecting fraudulent activities in financial and e-commerce transaction networks is crucial. One effective method for this is Densest Subgraph Discovery (DSD). However, deploying D…
RGL: A Graph-Centric, Modular Framework for Efficient Retrieval-Augmented Generation on Graphs
Yuan Li, Jun Hu, Jiaxin Jiang +3
Recent advances in graph learning have paved the way for innovative retrieval-augmented generation (RAG) systems that leverage the inherent relational structures in graph data. How…
Revisiting the Design of In-Memory Dynamic Graph Storage
Jixian Su, Chiyu Hao, Shixuan Sun +7
The effectiveness of in-memory dynamic graph storage (DGS) for supporting concurrent graph read and write queries is crucial for real-time graph analytics and updates. Various meth…