| 2025 | AAAI | Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs. | Jianxiang Yu, Yuxiang Ren, Chenghua Gong, Jiaqi Tan, Xiang Li, Xuecang Zhang |
| 2025 | AAAI | GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation. | Shengyin Sun, Wenhao Yu, Yuxiang Ren, Weitao Du, Liwei Liu, Xuecang Zhang, Ying Hu, Chen Ma |
| 2025 | ACL | STORM-BORN: A Challenging Mathematical Derivations Dataset Curated via a Human-in-the-Loop Multi-Agent Framework. | Wenhao Liu, Zhenyi Lu, Xinyu Hu, Jerry Zhang, Dailin Li, Jiacheng Cen, Huilin Cao, Haiteng Wang, Yuhan Li, Kun Xie, Dandan Li, Pei Zhang, Chengbo Zhang, Yuxiang Ren, Xiaohong Huang, Yan Ma |
| 2025 | DASFAA | Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs. | Shengyin Sun, Yuxiang Ren, Jiehao Chen, Chen Ma |
| 2025 | KDD | Advancing Graph Foundation Models: A Data-Centric Perspective. | Yuhan Li, Yuyao Wang, Jianheng Tang, Heng Chang, Yuxiang Ren, Jia Li |
| 2025 | WWW | G-Refer: Graph Retrieval-Augmented Large Language Model for Explainable Recommendation. | Yuhan Li, Xinni Zhang, Linhao Luo, Heng Chang, Yuxiang Ren, Irwin King, Jia Li |
| 2024 | DASFAA | Characterizing the Influence of Topology on Graph Learning Tasks. | Kailong Wu, Yule Xie, Jiaxin Ding, Yuxiang Ren, Luoyi Fu, Xinbing Wang, Chenghu Zhou |
| 2024 | DASFAA | CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. | Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang |
| 2024 | ICWS | LogRAG: Semi-Supervised Log-based Anomaly Detection with Retrieval-Augmented Generation. | Wanhao Zhang, Qianli Zhang, Enyu Yu, Yuxiang Ren, Yeqing Meng, Mingxi Qiu, Jilong Wang |
| 2024 | ISSRE | Leveraging RAG-Enhanced Large Language Model for Semi-Supervised Log Anomaly Detection. | Wanhao Zhang, Qianli Zhang, Enyu Yu, Yuxiang Ren, Yeqing Meng, Mingxi Qiu, Jilong Wang |
| 2023 | DASFAA | Decoupling Graph Neural Network with Contrastive Learning for Fraud Detection. | Lin Meng, Yuxiang Ren, Jiawei Zhang |
| 2023 | ISSRE | HRCA: A Heterogeneous Graph-based Adaptive Root Cause Analysis Framework. | Enyu Yu, Hui Dong, Yuxiang Ren, Minzhi Yan, Xuecang Zhang, Yi Yang, Le Yue, Zhengbin Huang |
| 2021 | DASFAA | Label Contrastive Coding Based Graph Neural Network for Graph Classification. | Yuxiang Ren, Jiyang Bai, Jiawei Zhang |
| 2021 | ICDE | EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph. | Yuxiang Ren, Hao Zhu, Jiawei Zhang, Peng Dai, Liefeng Bo |
| 2021 | IJCNN | Ripple Walk Training: A Subgraph-based Training Framework for Large and Deep Graph Neural Network. | Jiyang Bai, Yuxiang Ren, Jiawei Zhang |
| 2021 | IJCNN | BGADAM: Boosting based Genetic-Evolutionary ADAM for Neural Network Optimization. | Jiyang Bai, Yuxiang Ren, Jiawei Zhang |
| 2021 | IJCNN | Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention. | Yuxiang Ren, Jiawei Zhang |
| 2020 | ICDM | Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection. | Yuxiang Ren, Bo Wang, Jiawei Zhang, Yi Chang |
| 2019 | ICDE | Meta Diagram Based Active Social Networks Alignment. | Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang |