Robust Detection of Communities with Multi-semantics in Large Attributed Networks. - Di Jin 001; Ziyang Liu 004; Dongxiao He; Bogdan Gabrys; Katarzyna Musial (KSEM (1), 2018)

Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks. - Di Jin 001; Ziyang Liu 004; Weihao Li; Dongxiao He; Weixiong Zhang (AAAI, 2019)

BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search. - Yunjiang Jiang; Yue Shang; Ziyang Liu 004; Hongwei Shen; Yun Xiao; Wei Xiong; Sulong Xu; Weipeng Yan; Di Jin 001 (ICDM, 2020)

NF-VGA: Incorporating Normalizing Flows into Graph Variational Autoencoder for Embedding Attribute Networks. - Hongyu Shan; Di Jin 001; Pengfei Jiao; Ziyang Liu 004; Bingyi Li; Yuxiao Huang (ICDM, 2020)

BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks. - Di Jin 001; Xiangchen Song; Zhizhi Yu; Ziyang Liu 004; Heling Zhang; Zhaomeng Cheng; Jiawei Han 001 (CoRR, 2020)

AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks. - Zhizhi Yu; Di Jin 001; Ziyang Liu 004; Dongxiao He; Xiao Wang 017; Hanghang Tong; Jiawei Han 001 (ICDM, 2021)

BiTe-GCN: A New GCN Architecture via Bidirectional Convolution of Topology and Features on Text-Rich Networks. - Di Jin 001; Xiangchen Song; Zhizhi Yu; Ziyang Liu 004; Heling Zhang; Zhaomeng Cheng; Jiawei Han 001 (WSDM, 2021)

Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search. - Ziyang Liu 004; Zhaomeng Cheng; Yunjiang Jiang; Yue Shang; Wei Xiong; Sulong Xu; Bo Long; Di Jin 001 (CoRR, 2021)

Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search. - Ziyang Liu 004; Chaokun Wang; Hao Feng 007; Lingfei Wu 001; Liqun Yang (EMNLP (Industry Track), 2022)

TeKo: Text-Rich Graph Neural Networks with External Knowledge. - Zhizhi Yu; Di Jin 001; Jianguo Wei; Ziyang Liu 004; Yue Shang; Yun Xiao; Jiawei Han 001; Lingfei Wu 001 (CoRR, 2022)

Fast Unsupervised Graph Embedding via Graph Zoom Learning. - Ziyang Liu 004; Chaokun Wang; Yunkai Lou; Hao Feng 007 (ICDE, 2023)

Graph Contrastive Learning with Generative Adversarial Network. - Cheng Wu; Chaokun Wang; Jingcao Xu; Ziyang Liu 004; Kai Zheng 001; Xiaowei Wang; Yang Song 008; Kun Gai (KDD, 2023)

PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation. - Ziyang Liu 004; Chaokun Wang; Jingcao Xu; Cheng Wu; Kai Zheng 001; Yang Song 008; Na Mou; Kun Gai (CoRR, 2023)

Embedding text-rich graph neural networks with sequence and topical semantic structures. - Zhizhi Yu; Di Jin 001; Ziyang Liu 004; Dongxiao He; Xiao Wang 017; Hanghang Tong; Jiawei Han 001 (Knowl. Inf. Syst., 2023)

Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation. - Hongwei Li; Chaokun Wang; Ziyang Liu 004 (APWeb/WAIM (3), 2024)

GraphHI: Boosting Graph Neural Networks for Large-Scale Graphs. - Hao Feng 007; Chaokun Wang; Ziyang Liu 004; Yunkai Lou; Zhenyu Liu; Xiaokun Zhu; Yongjun Bao; Weipeng Yan (ICDE, 2024)

Incorporating Dynamic Temperature Estimation into Contrastive Learning on Graphs. - Ziyang Liu 004; Chaokun Wang; Liqun Yang; Yunkai Lou; Hao Feng 007; Cheng Wu; Kai Zheng 001; Yang Song 008 (ICDE, 2024)

Graph Contrastive Learning with Reinforcement Augmentation. - Ziyang Liu 004; Chaokun Wang; Cheng Wu (IJCAI, 2024)

Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework. - Cheng Wu; Shaoyun Shi; Chaokun Wang; Ziyang Liu 004; Wang Peng; Wenjin Wu; Dongying Kong; Han Li 005; Kun Gai (WWW, 2024)

TeKo: Text-Rich Graph Neural Networks With External Knowledge. - Zhizhi Yu; Di Jin 001; Jianguo Wei; Yawen Li 001; Ziyang Liu 004; Yue Shang; Jiawei Han 001; Lingfei Wu 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Efficient Unsupervised Graph Embedding With Attributed Graph Reduction and Dual-Level Loss. - Ziyang Liu 004; Chaokun Wang; Hao Feng 007; Ziyang Chen (IEEE Trans. Knowl. Data Eng., 2024)

Learning Multiple User Distributions for Recommendation via Guided Conditional Diffusion. - Cheng Wu; Liang Su; Chaokun Wang; Shaoyun Shi; Ziqian Zhang; Ziyang Liu 004; Wang Peng; Wenjin Wu; Peng Jiang (AAAI, 2025)

TeRDy: Temporal Relation Dynamics through Frequency Decomposition for Temporal Knowledge Graph Completion. - Ziyang Liu 004; Chaokun Wang (ACL (1), 2025)

Efficient Unsupervised Graph Embedding with Attributed Graph Reduction and Dual-Level Loss: (Extended Abstract). - Ziyang Liu 004; Chaokun Wang; Hao Feng 007; Ziyang Chen (ICDE, 2025)

Effective and Scalable Heterogeneous Graph Neural Network Framework with Convolution-oriented Attention. - Ziqian Zhang; Chaokun Wang; Shuwen Zheng; Cheng Wu; Ziyang Liu 004; Hao Feng 007 (ICDE, 2025)

Balancing Self-Presentation and Self-Hiding for Exposure-Aware Recommendation Based on Graph Contrastive Learning. - Leqi Zheng; Chaokun Wang; Ziyang Liu 004; Canzhi Chen; Cheng Wu; Hongwei Li (SIGIR, 2025)

Pone-GNN: Integrating Positive and Negative Feedback in Graph Neural Networks for Recommender Systems. - Ziyang Liu 004; Chaokun Wang; Shuwen Zheng; Cheng Wu; Kai Zheng 001; Yang Song 008; Na Mou (Trans. Recomm. Syst., 2025)