| 2026 | AAAI | PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths. | Boyu Chen, Zirui Guo, Zidan Yang, Yuluo Chen, Junze Chen, Zhenghao Liu, Chuan Shi, Cheng Yang |
| 2026 | ACL | CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding. | Zeqi Chen, Zhaoyang Chu, Yi Gui, Feng Guo, Yao Wan, Chuan Shi |
| 2026 | ACL | MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing. | Yang Liu, Jinxuan Cai, Yishen Li, Qi Meng, Zedi Liu, Xin Li, Chen Qian, Chuan Shi, Cheng Yang |
| 2026 | DASFAA | Unleashing the Power of Pre-trained Graph Models in Federated Graph Learning. | Huabin Sun, Bo Yan, Yaoqi Liu, Shaohua Fan, Yang Cao, Chuan Shi |
| 2026 | WWW | Spattack: Subgroup Poisoning Attacks on Federated Recommender Systems. | Bo Yan, Yurong Hao, Dingqi Liu, Huabin Sun, Pengpeng Qiao, Wei Yang Bryan Lim, Yang Cao, Chuan Shi |
| 2026 | WWW | Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning. | Zhongjian Zhang, Xiao Wang, Mengmei Zhang, Jiarui Tan, Chuan Shi |
| 2026 | WWW | FRiskGPT: A Generative Foundation Model for Financial Risk Detection. | Zhongjian Zhang, Mengmei Zhang, Dehua Xu, Rongjun Shi, Jianfeng Liu, Fuli Meng, Huajian Xu, Xiao Wang, Ruijia Wang, Junze Chen, Minwei Tang, Chuan Shi |
| 2026 | WWW | Riemannian Graph Tokenizer for Structural Knowledge Transfer. | Qimin Zhou, Haibo Liu, Yujie Wang, Li Sun, Chuan Shi |
| 2026 | WSDM | C | Yue Yu, Ting Bai, Hengzhi Lan, Li Qian, Li Peng, Jie Wu, Wei Liu, Jian Luan, Chuan Shi |
| 2025 | AAAI | Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer. | Jinyu Yang, Ruijia Wang, Cheng Yang, Bo Yan, Qimin Zhou, Yang Juan, Chuan Shi |
| 2025 | AAAI | Federated Graph Condensation with Information Bottleneck Principles. | Bo Yan, Sihao He, Cheng Yang, Shang Liu, Yang Cao, Chuan Shi |
| 2025 | AAAI | Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction. | Xinlong Zhai, Chunchen Wang, Ruijia Wang, Jiazheng Kang, Shujie Li, Boyu Chen, Tengfei Ma, Zikai Zhou, Cheng Yang, Chuan Shi |
| 2025 | AAAI | Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective. | Zhongjian Zhang, Mengmei Zhang, Xiao Wang, Lingjuan Lyu, Bo Yan, Junping Du, Chuan Shi |
| 2025 | ACL | Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases. | Michael Y. Hu, Jackson Petty, Chuan Shi, William Merrill, Tal Linzen |
| 2025 | ADMA | Prompt-Tuning on Heterogeneous Information Networks for Cold-Start Recommendation. | Junfei Bao, Yanhu Mo, Bo Yan, Hai Huang, Chuan Shi |
| 2025 | ASPDAC | PIRLLS: Pretraining with Imitation and RL Finetuning for Logic Synthesis. | Guande Dong, Jianwang Zhai, Hongtao Cheng, Xiao Yang, Chuan Shi, Kang Zhao |
| 2025 | CIKM | Data-centric Prompt Tuning for Dynamic Graphs. | Yufei Peng, Cheng Yang, Zhengjie Fan, Chuan Shi |
| 2025 | CIKM | Full-Atom Protein-Protein Interaction Prediction via Atomic Equivariant Attention Network. | Chunchen Wang, Cheng Yang, Wenchuan Yang, Le Song, Chuan Shi |
| 2025 | DAC | IRGNN: A Graph-based Framework Integrating Numerical Solution and Point Cloud for Static IR Drop Prediction. | Feng Guo, Yueyue Xi, Jianwang Zhai, Jingyu Jia, Jiawei Liu, Kang Zhao, Chuan Shi |
| 2025 | DATE | IR-Fusion: A Fusion Framework for Static IR Drop Analysis Combining Numerical Solution and Machine Learning. | Feng Guo, Jianwang Zhai, Jingyu Jia, Jiawei Liu, Kang Zhao, Bei Yu, Chuan Shi |
| 2025 | DATE | WideGate: Beyond Directed Acyclic Graph Learning in Subcircuit Boundary Prediction. | Jiawei Liu, Zhiyan Liu, Xun He, Jianwang Zhai, Zhengyuan Shi, Qiang Xu, Bei Yu, Chuan Shi |
| 2025 | ICASSP | Speech-based Clinical Depression Detection: An Empirical Study. | Yangbin Chen, Chenyang Xu, Chunfeng Liang, Yanbao Tao, Chuan Shi |
| 2025 | ICASSP | A Weighted Cross-entropy Loss for Mitigating LLM Hallucinations in Cross-lingual Continual Pretraining. | Yuantao Fan, Ruifan Li, Guangwei Zhang, Chuan Shi, Xiaojie Wang |
| 2025 | ICCAD | Transferable Parasitic Estimation via Graph Contrastive Learning and Label Rebalancing in AMS Circuits. | Shan Shen, Shenglu Hua, Jiajun Zou, Jiawei Liu, Jianwang Zhai, Chuan Shi, Wenjian Yu |
| 2025 | KDD | Graph Positional Autoencoders as Self-supervised Learners. | Yang Liu, Deyu Bo, Wenxuan Cao, Yuan Fang, Yawen Li, Chuan Shi |
| 2025 | KDD | GraphLAMA: Enabling Efficient Adaptation of Graph Language Models with Limited Annotations. | Junze Chen, Cheng Yang, Shujie Li, Zhiqiang Zhang, Yawen Li, Junping Du, Chuan Shi |
| 2025 | KDD | Advancing Molecular Graph-Text Pre-training via Fine-grained Alignment. | Yibo Li, Yuan Fang, Mengmei Zhang, Chuan Shi |
| 2025 | KDD | FLAG: Fraud Detection with LLM-enhanced Graph Neural Network. | Chengdong Yang, Hongrui Liu, Daixin Wang, Zhiqiang Zhang, Cheng Yang, Chuan Shi |
| 2025 | KDD | Benchmarking Graph Foundation Models. | Jinyu Yang, Liangwei Yang, Zeyuan Guo, Jiayi Gao, Jing Wu, Tianhao Chai, Hai Huang, Cheng Yang, Chuan Shi |
| 2025 | KDD | Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks? | Zhongjian Zhang, Xiao Wang, Huichi Zhou, Yue Yu, Mengmei Zhang, Cheng Yang, Chuan Shi |
| 2025 | NAACL | Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training. | Sun Ao, Weilin Zhao, Xu Han, Cheng Yang, Xinrong Zhang, Zhiyuan Liu, Chuan Shi, Maosong Sun |
| 2025 | NAACL | Exploring the Potential of Large Language Models for Heterophilic Graphs. | Yuxia Wu, Shujie Li, Yuan Fang, Chuan Shi |
| 2025 | WWW | Artificial Intelligence for Complex Network: Potential, Methodology and Application. | Jingtao Ding, Yu Zheng, Huandong Wang, Carlo Vittorio Cannistraci, Jianxi Gao, Yong Li, Chuan Shi |
| 2025 | SIGIR | CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models. | Junze Chen, Xinjie Yang, Cheng Yang, Junfei Bao, Zeyuan Guo, Yawen Li, Chuan Shi |
| 2025 | SC | BurstEngine: An efficient distributed framework for training transformers On extremely Long sequences of over 1M tokens. | Ao Sun, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong Sun |
| 2024 | AAAI | Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization. | Tianrui Jia, Haoyang Li, Cheng Yang, Tao Tao, Chuan Shi |
| 2024 | AAAI | A Generalized Neural Diffusion Framework on Graphs. | Yibo Li, Xiao Wang, Hongrui Liu, Chuan Shi |
| 2024 | AAAI | Graph Contrastive Invariant Learning from the Causal Perspective. | Yanhu Mo, Xiao Wang, Shaohua Fan, Chuan Shi |
| 2024 | AAAI | FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization. | Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi |
| 2024 | DASFAA | Learning Social Graph for Inactive User Recommendation. | Nian Liu, Shen Fan, Ting Bai, Peng Wang, Mingwei Sun, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Chuan Shi |
| 2024 | ICCAD | PolarGate: Breaking the Functionality Representation Bottleneck of And-Inverter Graph Neural Network. | Jiawei Liu, Jianwang Zhai, Mingyu Zhao, Zhe Lin, Bei Yu, Chuan Shi |
| 2024 | ICML | Graph Distillation with Eigenbasis Matching. | Yang Liu, Deyu Bo, Chuan Shi |
| 2024 | ICML | Less is More: on the Over-Globalizing Problem in Graph Transformers. | Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi |
| 2024 | IJCAI | Heterogeneous Graph Transformer with Poly-Tokenization. | Zhiyuan Lu, Yuan Fang, Cheng Yang, Chuan Shi |
| 2024 | KDD | Customizing Graph Neural Network for CAD Assembly Recommendation. | Fengqi Liang, Huan Zhao, Yuhan Quan, Wei Fang, Chuan Shi |
| 2024 | KDD | Advancing Molecule Invariant Representation via Privileged Substructure Identification. | Ruijia Wang, Haoran Dai, Cheng Yang, Le Song, Chuan Shi |
| 2024 | WWW | Graph Fairness Learning under Distribution Shifts. | Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi |
| 2024 | WWW | Lecture-style Tutorial: Towards Graph Foundation Models. | Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu |
| 2024 | WWW | Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation. | Bo Yan, Yang Cao, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi |
| 2024 | WWW | Calibrating Graph Neural Networks from a Data-centric Perspective. | Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou |
| 2024 | WWW | GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. | Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi |
| 2024 | WWW | Endowing Pre-trained Graph Models with Provable Fairness. | Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi |
| 2023 | AAAI | Directed Acyclic Graph Structure Learning from Dynamic Graphs. | Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi |
| 2023 | AAAI | MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning. | Xumeng Gong, Cheng Yang, Chuan Shi |
| 2023 | CIKM | Retrieving GNN Architecture for Collaborative Filtering. | Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi |
| 2023 | CIKM | Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks. | Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi |
| 2023 | CIKM | Node-dependent Semantic Search over Heterogeneous Graph Neural Networks. | Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi |
| 2023 | DASFAA | Memory-Enhanced Period-Aware Graph Neural Network for General POI Recommendation. | Tianchi Yang, Haihan Gao, Cheng Yang, Chuan Shi, Qianlong Xie, Xingxing Wang, Dong Wang |
| 2023 | ICASSP | Clustering-Based Supervised Contrastive Learning for Identifying Risk Items on Heterogeneous Graph. | Ao Li, Yugang Ji, Guanyi Chu, Xiao Wang, Dong Li, Chuan Shi |
| 2023 | ICLR | Specformer: Spectral Graph Neural Networks Meet Transformers. | Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao |
| 2023 | KDD | A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability. | Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du |
| 2023 | WWW | A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. | Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu |
| 2023 | WWW | Minimum Topology Attacks for Graph Neural Networks. | Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du |
| 2023 | SIGIR | Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. | Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi |
| 2023 | SIGIR | GammaGL: A Multi-Backend Library for Graph Neural Networks. | Yaoqi Liu, Cheng Yang, Tianyu Zhao, Hui Han, Siyuan Zhang, Jing Wu, Guangyu Zhou, Hai Huang, Hui Wang, Chuan Shi |
| 2023 | WSDM | Knowledge-Adaptive Contrastive Learning for Recommendation. | Hao Wang, Yao Xu, Cheng Yang, Chuan Shi, Xin Li, Ning Guo, Zhiyuan Liu |
| 2023 | WSDM | Learning to Distill Graph Neural Networks. | Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin |
| 2023 | SDM | Abnormal Event Detection via Hypergraph Contrastive Learning. | Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang |
| 2022 | AAAI | Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations. | Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou |
| 2022 | AAAI | Robust Heterogeneous Graph Neural Networks against Adversarial Attacks. | Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou |
| 2022 | CIKM | OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network. | Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi |
| 2022 | DASFAA | Gated Hypergraph Neural Network for Scene-Aware Recommendation. | Tianchi Yang, Luhao Zhang, Chuan Shi, Cheng Yang, Siyong Xu, Ruiyu Fang, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang |
| 2022 | DASFAA | A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation. | Luhao Zhang, Ruiyu Fang, Tianchi Yang, Maodi Hu, Tao Li, Chuan Shi, Dong Wang |
| 2022 | IJCAI | Self-supervised Graph Neural Networks for Multi-behavior Recommendation. | Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao |
| 2022 | IJCAI | Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. | Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun |
| 2022 | WWW | Prohibited Item Detection via Risk Graph Structure Learning. | Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du |
| 2022 | WWW | Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. | Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou |
| 2022 | WWW | Compact Graph Structure Learning via Mutual Information Compression. | Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi |
| 2022 | SIGIR | Co-clustering Interactions via Attentive Hypergraph Neural Network. | Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang |
| 2022 | SIGIR | Geometric Disentangled Collaborative Filtering. | Yiding Zhang, Chaozhuo Li, Xing Xie, Xiao Wang, Chuan Shi, Yuming Liu, Hao Sun, Liangjie Zhang, Weiwei Deng, Qi Zhang |
| 2022 | SIGIR | Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. | Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi |
| 2022 | WSDM | Profiling the Design Space for Graph Neural Networks based Collaborative Filtering. | Zhenyi Wang, Huan Zhao, Chuan Shi |
| 2022 | WSDM | Few-shot Link Prediction in Dynamic Networks. | Cheng Yang, Chunchen Wang, Yuanfu Lu, Xumeng Gong, Chuan Shi, Wei Wang, Xu Zhang |
| 2021 | AAAI | Beyond Low-frequency Information in Graph Convolutional Networks. | Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen |
| 2021 | AAAI | Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. | Houye Ji, Junxiong Zhu, Xiao Wang, Chuan Shi, Bai Wang, Xiaoye Tan, Yanghua Li, Shaojian He |
| 2021 | AAAI | GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks. | Yi Li, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi, Yiming Wang |
| 2021 | AAAI | Learning to Pre-train Graph Neural Networks. | Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi |
| 2021 | AAAI | Heterogeneous Graph Structure Learning for Graph Neural Networks. | Jianan Zhao, Xiao Wang, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye |
| 2021 | ACL | Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge. | Linmei Hu, Tianchi Yang, Luhao Zhang, Wanjun Zhong, Duyu Tang, Chuan Shi, Nan Duan, Ming Zhou |
| 2021 | CIKM | Contrastive Pre-Training of GNNs on Heterogeneous Graphs. | Xunqiang Jiang, Yuanfu Lu, Yuan Fang, Chuan Shi |
| 2021 | CIKM | Prohibited Item Detection on Heterogeneous Risk Graphs. | Yugang Ji, Chuan Shi, Xiao Wang |
| 2021 | CIKM | Neural Information Diffusion Prediction with Topic-Aware Attention Network. | Hao Wang, Cheng Yang, Chuan Shi |
| 2021 | CIKM | Topic-aware Heterogeneous Graph Neural Network for Link Prediction. | Siyong Xu, Cheng Yang, Chuan Shi, Yuan Fang, Yuxin Guo, Tianchi Yang, Luhao Zhang, Maodi Hu |
| 2021 | ICDE | Structure-Aware Parameter-Free Group Query via Heterogeneous Information Network Transformer. | Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Chuan Shi, Philip S. Yu, Ming-Syan Chen |
| 2021 | ICDM | Heterogeneous Graph Neural Network with Distance Encoding. | Houye Ji, Cheng Yang, Chuan Shi, Pan Li |
| 2021 | IJCAI | CuCo: Graph Representation with Curriculum Contrastive Learning. | Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang |
| 2021 | KDD | Pre-training on Large-Scale Heterogeneous Graph. | Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang |
| 2021 | KDD | Graph Representation Learning: Foundations, Methods, Applications and Systems. | Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu |
| 2021 | KDD | The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). | Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang |
| 2021 | KDD | Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. | Xiao Wang, Nian Liu, Hui Han, Chuan Shi |
| 2021 | PAKDD | Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction. | Tianchi Yang, Linmei Hu, Luhao Zhang, Chuan Shi, Cheng Yang, Nan Duan, Ming Zhou |
| 2021 | WWW | Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. | Cheng Yang, Jiawei Liu, Chuan Shi |
| 2021 | WWW | Large-scale Comb-K Recommendation. | Houye Ji, Junxiong Zhu, Chuan Shi, Xiao Wang, Bai Wang, Chaoyu Zhang, Zixuan Zhu, Feng Zhang, Yanghua Li |
| 2021 | WWW | Graph Structure Estimation Neural Networks. | Ruijia Wang, Shuai Mou, Xiao Wang, Wanpeng Xiao, Qi Ju, Chuan Shi, Xing Xie |
| 2021 | WWW | Lorentzian Graph Convolutional Networks. | Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song |
| 2021 | WWW | Interpreting and Unifying Graph Neural Networks with An Optimization Framework. | Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui |
| 2021 | SIGIR | Package Recommendation with Intra- and Inter-Package Attention Networks. | Chen Li, Yuanfu Lu, Wei Wang, Chuan Shi, Ruobing Xie, Haili Yang, Cheng Yang, Xu Zhang, Leyu Lin |
| 2021 | SDM | Sequence-aware Heterogeneous Graph Neural Collaborative Filtering. | Chen Li, Linmei Hu, Chuan Shi, Guojie Song, Yuanfu Lu |
| 2020 | AAAI | GraLSP: Graph Neural Networks with Local Structural Patterns. | Yilun Jin, Guojie Song, Chuan Shi |
| 2020 | AAAI | FlowScope: Spotting Money Laundering Based on Graphs. | Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng |
| 2020 | AAAI | Multi-Component Graph Convolutional Collaborative Filtering. | Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li |
| 2020 | ACL | Graph Neural News Recommendation with Unsupervised Preference Disentanglement. | Linmei Hu, Siyong Xu, Chen Li, Cheng Yang, Chuan Shi, Nan Duan, Xing Xie, Ming Zhou |
| 2020 | ADMA | STCNet: Spatial-Temporal Convolution Network for Traffic Speed Prediction. | Mingjun Ma, Bo Peng, Ding Xiao, Yugang Ji, Chuan Shi |
| 2020 | ADMA | Encrypted Traffic Classification Using Graph Convolutional Networks. | Shuang Mo, Yifei Wang, Ding Xiao, Wenrui Wu, Shaohua Fan, Chuan Shi |
| 2020 | CIKM | More Than One: A Cluster-Prototype Matching Framework for Zero-Shot Learning. | Jing Zhang, Yangli-ao Geng, Qingyong Li, Chuan Shi |
| 2020 | CIKM | EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning. | Zhiqiang Zhang, Jun Zhou, Chuan Shi |
| 2020 | ICDM | Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. | Yujie Fan, Yanfang Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, Liang Zhao |
| 2020 | ICDM | Learning Node Representations from Noisy Graph Structures. | Junshan Wang, Ziyao Li, Qingqing Long, Weiyu Zhang, Guojie Song, Chuan Shi |
| 2020 | ICDM | Adversarial Label-Flipping Attack and Defense for Graph Neural Networks. | Mengmei Zhang, Linmei Hu, Chuan Shi, Xiao Wang |
| 2020 | IJCAI | Decorrelated Clustering with Data Selection Bias. | Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang |
| 2020 | IJCAI | Network Schema Preserving Heterogeneous Information Network Embedding. | Jianan Zhao, Xiao Wang, Chuan Shi, Zekuan Liu, Yanfang Ye |
| 2020 | KDD | AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. | Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei |
| 2020 | KDD | Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. | Yuanfu Lu, Yuan Fang, Chuan Shi |
| 2020 | WWW | Structural Deep Clustering Network. | Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui |
| 2020 | WWW | One2Multi Graph Autoencoder for Multi-view Graph Clustering. | Shaohua Fan, Xiao Wang, Chuan Shi, Emiao Lu, Ken Lin, Bai Wang |
| 2020 | SDM | Multiplex Memory Network for Collaborative Filtering. | Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi |
| 2019 | AAAI | Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism. | Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi |
| 2019 | AAAI | Relation Structure-Aware Heterogeneous Information Network Embedding. | Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu |
| 2019 | AAAI | Hyperbolic Heterogeneous Information Network Embedding. | Xiao Wang, Yiding Zhang, Chuan Shi |
| 2019 | ADMA | Spatial-Temporal Recurrent Neural Network for Anomalous Trajectories Detection. | Yunyao Cheng, Bin Wu, Li Song, Chuan Shi |
| 2019 | APWEB | Coupled Semi-supervised Clustering: Exploring Attribute Correlations in Heterogeneous Information Networks. | Jianan Zhao, Ding Xiao, Linmei Hu, Chuan Shi |
| 2019 | CIKM | Temporal Network Embedding with Micro- and Macro-dynamics. | Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye |
| 2019 | CIKM | Recent Developments of Deep Heterogeneous Information Network Analysis. | Chuan Shi, Philip S. Yu |
| 2019 | CIKM | HENA 2019: The 3rd Workshop of Heterogeneous Information Network Analysis and Applications. | Chuan Shi, Yanfang Ye, Jiawei Zhang |
| 2019 | CIKM | Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework. | Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Chuan Shi |
| 2019 | CIKM | Author Set Identification via Quasi-Clique Discovery. | Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye |
| 2019 | EMNLP | Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification. | Linmei Hu, Tianchi Yang, Chuan Shi, Houye Ji, Xiaoli Li |
| 2019 | EMNLP | Improving Distantly-Supervised Relation Extraction with Joint Label Embedding. | Linmei Hu, Luhao Zhang, Chuan Shi, Liqiang Nie, Weili Guan, Cheng Yang |
| 2019 | ICNC | Credibility Assessment of Simulation Models Using Hesitant Cloud Linguistic Term Sets. | Xiaojun Yang, Zhongfu Xu, Chuan Shi, Hao Lei, Changwei Yan |
| 2019 | IJCAI | iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. | Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu |
| 2019 | KDD | Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. | Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma, Yongliang Li |
| 2019 | KDD | Adversarial Learning on Heterogeneous Information Networks. | Binbin Hu, Yuan Fang, Chuan Shi |
| 2019 | PAKDD | Integrating Topic Model and Heterogeneous Information Network for Aspect Mining with Rating Bias. | Yugang Ji, Chuan Shi, Fuzhen Zhuang, Philip S. Yu |
| 2019 | PAKDD | NEAR: Normalized Network Embedding with Autoencoder for Top-K Item Recommendation. | Dedong Li, Aimin Zhou, Chuan Shi |
| 2019 | WWW | Heterogeneous Graph Attention Network. | Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Yanfang Ye, Peng Cui, Philip S. Yu |
| 2019 | WWW | Your Style Your Identity: Leveraging Writing and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network. | Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong |
| 2018 | ADMA | Anomalous Trajectory Detection Using Recurrent Neural Network. | Li Song, Ruijia Wang, Ding Xiao, Xiaotian Han, Yanan Cai, Chuan Shi |
| 2018 | ADMA | Abstractive Document Summarization via Bidirectional Decoder. | Xin Wan, Chen Li, Ruijia Wang, Ding Xiao, Chuan Shi |
| 2018 | APWEB | Representation Learning with Depth and Breadth for Recommendation Using Multi-view Data. | Xiaotian Han, Chuan Shi, Lei Zheng, Philip S. Yu, Jianxin Li, Yuanfu Lu |
| 2018 | APWEB | Matrix Factorization Meets Social Network Embedding for Rating Prediction. | Menghao Zhang, Binbin Hu, Chuan Shi, Bin Wu, Bai Wang |
| 2018 | CIKM | Abnormal Event Detection via Heterogeneous Information Network Embedding. | Shaohua Fan, Chuan Shi, Xiao Wang |
| 2018 | CIKM | Local and Global Information Fusion for Top-N Recommendation in Heterogeneous Information Network. | Binbin Hu, Chuan Shi, Wayne Xin Zhao, Tianchi Yang |
| 2018 | IJCAI | NeuCast: Seasonal Neural Forecast of Power Grid Time Series. | Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang, Xueqi Cheng |
| 2018 | IJCAI | Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. | Xiaotian Han, Chuan Shi, Senzhang Wang, Philip S. Yu, Li Song |
| 2018 | KDD | Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model. | Binbin Hu, Chuan Shi, Wayne Xin Zhao, Philip S. Yu |
| 2018 | PAKDD | A Heterogeneous Information Network Method for Entity Set Expansion in Knowledge Graph. | Xiaohuan Cao, Chuan Shi, Yuyan Zheng, Jiayu Ding, Xiaoli Li, Bin Wu |
| 2018 | PRICAI | Attention Based Meta Path Fusion for Heterogeneous Information Network Embedding. | Houye Ji, Chuan Shi, Bai Wang |
| 2017 | CEC | A decomposition based multiobjective evolutionary algorithm with semi-supervised classification. | Xiaoji Chen, Chuan Shi, Aimin Zhou, Bin Wu, Zixing Cai |
| 2017 | CIKM | Local Ensemble across Multiple Sources for Collaborative Filtering. | Jing Zheng, Fuzhen Zhuang, Chuan Shi |
| 2017 | PAKDD | Personalized Ranking Recommendation via Integrating Multiple Feedbacks. | Jian Liu, Chuan Shi, Binbin Hu, Shenghua Liu, Philip S. Yu |
| 2017 | PAKDD | DSBPR: Dual Similarity Bayesian Personalized Ranking. | Longfei Shi, Bin Wu, Jing Zheng, Chuan Shi, Mengxin Li |
| 2017 | PAKDD | Entity Set Expansion with Meta Path in Knowledge Graph. | Yuyan Zheng, Chuan Shi, Xiaohuan Cao, Xiaoli Li, Bin Wu |
| 2017 | WWW | Local Low-Rank Matrix Approximation with Preference Selection of Anchor Points. | Menghao Zhang, Binbin Hu, Chuan Shi, Bai Wang |
| 2016 | PAKDD | Link Prediction in Schema-Rich Heterogeneous Information Network. | Xiaohuan Cao, Yuyan Zheng, Chuan Shi, Jingzhi Li, Bin Wu |
| 2016 | PAKDD | Dual Similarity Regularization for Recommendation. | Jing Zheng, Jian Liu, Chuan Shi, Fuzhen Zhuang, Jingzhi Li, Bin Wu |
| 2016 | RecSys | RecExp: A Semantic Recommender System with Explanation Based on Heterogeneous Information Network. | Jiawei Hu, Zhiqiang Zhang, Jian Liu, Chuan Shi, Philip S. Yu, Bai Wang |
| 2015 | CIKM | Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks. | Chuan Shi, Zhiqiang Zhang, Ping Luo, Philip S. Yu, Yading Yue, Bin Wu |
| 2015 | ICDM | Dynamic Community Detection Algorithm Based on Incremental Identification. | Xiaoming Li, Bin Wu, Qian Guo, Xuelin Zeng, Chuan Shi |
| 2014 | APWEB | Relevance Measure in Large-Scale Heterogeneous Networks. | Xiaofeng Meng, Chuan Shi, Yitong Li, Lei Zhang, Bin Wu |
| 2014 | CIKM | Ranking-based Clustering on General Heterogeneous Information Networks by Network Projection. | Chuan Shi, Ran Wang, Yitong Li, Philip S. Yu, Bin Wu |
| 2014 | ICDM | A Retweet Number Prediction Model Based on Followers' Retweet Intention and Influence. | Huidong Zhao, Gang Liu, Chuan Shi, Bin Wu |
| 2014 | KDD | A Fast Distributed Stochastic Gradient Descent Algorithm for Matrix Factorization. | Fanglin Li, Bin Wu, Liutong Xu, Chuan Shi, Jing Shi |
| 2013 | ADMA | Multi-Objective Optimization for Overlapping Community Detection. | Jingfei Du, Jianyang Lai, Chuan Shi |
| 2013 | PAKDD | Integrating Clustering and Ranking on Hybrid Heterogeneous Information Network. | Ran Wang, Chuan Shi, Philip S. Yu, Bin Wu |
| 2012 | EDBT | Relevance search in heterogeneous networks. | Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu |
| 2012 | ICWSM | War Versus Inspirational in Forrest Gump: Cultural Effects in Tagging Communities. | Zhenhua Dong, Chuan Shi, Shilad Sen, Loren G. Terveen, John Riedl |
| 2012 | KDD | HeteRecom: a semantic-based recommendation systemin heterogeneous networks. | Chuan Shi, Chong Zhou, Xiangnan Kong, Philip S. Yu, Gang Liu, Bai Wang |
| 2012 | SDM | Multi-Objective Multi-Label Classification. | Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang |
| 2011 | ADMA | A Novel Genetic Algorithm for Overlapping Community Detection. | Yanan Cai, Chuan Shi, Yuxiao Dong, Qing Ke, Bin Wu |
| 2011 | CEC | Multi-objective decisionmaking in the detection of comprehensive community structures. | Chuan Shi, Zhenyu Yan, Xin Pan, Yanan Cai, Bin Wu |
| 2011 | CEC | An estimation of distribution algorithm based on nonparametric density estimation. | Luhan Zhou, Aimin Zhou, Guixu Zhang, Chuan Shi |
| 2011 | CIKM | On selection of objective functions in multi-objective community detection. | Chuan Shi, Philip S. Yu, Yanan Cai, Zhenyu Yan, Bin Wu |
| 2010 | ADMA | A Novel Algorithm for Hierarchical Community Structure Detection in Complex Networks. | Chuan Shi, Jian Zhang, Liangliang Shi, Yanan Cai, Bin Wu |
| 2010 | CEC | A multi-objective approach for community detection in complex network. | Chuan Shi, Cha Zhong, Zhenyu Yan, Yanan Cai, Bin Wu |
| 2010 | ICDM | A Comparison of Objective Functions in Network Community Detection. | Chuan Shi, Yanan Cai, Philip S. Yu, Zhenyu Yan, Bin Wu |
| 2009 | ADMA | VisNetMiner: An Integration Tool for Visualization and Analysis of Networks. | Chuan Shi, Dan Zhou, Bin Wu, Jian Liu |
| 2007 | ICDM | An Efficient Fitness Assignment Based on Dominating Tree. | Chuan Shi, Zhongzhi Shi, Bin Wu |
| 2006 | ISNN | Stock Time Series Forecasting Using Support Vector Machines Employing Analyst Recommendations. | Zhiyong Zhang, Chuan Shi, Sulan Zhang, Zhongzhi Shi |
| 2006 | PRICAI | An Improved Multiobjective Evolutionary Algorithm Based on Dominating Tree. | Chuan Shi, Qingyong Li, Zhiyong Zhang, Zhongzhi Shi |
| 2006 | PRIMA | A Multi-agent Negotiation Model Applied in Multi-objective Optimization. | Chuan Shi, Jiewen Luo, Fen Lin |
| 2003 | CEC | A new simple and highly efficient multi-objective optimal evolutionary algorithm. | Chuan Shi, Yan Li, Lishan Kang |