Chuxu Zhang

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Publication

Underlined authors are students advised or mentored by me.

Preprint

• Knowledge Distillation on Graphs: A Survey
  arXiv preprint arXiv:2302.00219

• Adversarial Cross-View Disentangled Graph Contrastive Learning
  arXiv preprint arXiv:2209.07699
  NeurIPS'22 Workshop: New Frontiers in Graph Learning

2023

• When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations
  C. Zhang, C. Huang, Y. Tian, Q. Wen, Z. Ouyang, Y. Li, Y. Ye, C. Zhang
  [ICML'23] The International Conference on Machine Learning
  Original Version in NeurIPS'22 Workshop: New Frontiers in Graph Learning
  Best Paper Runner-up Award at AAAI'23 DCAA Workshop

• Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
  M. Ju, T. Zhao, Q. Wen, W. Yu, N. Shah, Y. Ye, C. Zhang
  [ICLR'23] The International Conference on Learning Representations

• Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
  C. Zhang, Y. Tian, M. Ju, Z. Liu, Y. Ye, N. Chawla, C. Zhang
  [ICLR'23] The International Conference on Learning Representations

• Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
  Y. Tian, C. Zhang, Z. Guo, X. Zhang, N. Chawla
  [ICLR'23] The International Conference on Learning Representations
  Spotlight, Original Version in NeurIPS'22 Workshop: New Frontiers in Graph Learning

• Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning
  C. Zhang, H. Liu, J. Li, Y. Ye, C. Zhang
  [TMLR] Transactions on Machine Learning Research
  Original Version in NeurIPS'22 Workshop: New Frontiers in Graph Learning

• Hypergraph Contrastive Learning for Drug Trafficking Community Detection
  T. Ma, Y. Qian, C. Zhang, Y. Ye
  [ICDM'23] The IEEE International Conference on Data Mining

• Heterogeneous Temporal Graph Neural Network Explainer
  J. Li, C. Zhang, C. Zhang
  [CIKM'23] The ACM International Conference on Information and Knowledge Management

• A Multi-Modality Framework for Drug-Drug Interaction Prediction by Harnessing Multi-source Data
  Q. Wen, J. Li, C. Zhang, Y. Ye
  [CIKM'23] The ACM International Conference on Information and Knowledge Management

• Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation
  Q. Yang, C. Ma, Q. Zhang, X. Gao, C. Zhang, X. Zhang
  [KDD'23] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Graph-based Molecular Representation Learning
  Z. Guo, K. Guo, B. Nan, Y. Tian, Y. Ma, O. Wiest, X. Zhang, W. Wang, C. Zhang, N. Chawla
  [IJCAI'23] The International Joint Conference on Artificial Intelligence

• Fair Graph Representation Learning via Diverse Mixture of Experts
  Z. Liu, C. Zhang, Y. Tian, E. Zhang, C. Huang, Y. Ye. C. Zhang
  [WWW'23] The Web Conference/World Wide Web Conference

• Multi-Modal Adversarial Self-Supervised Learning for Recommendation
  W. Wei, C. Huang, L. Xia, C. Zhang
  [WWW'23] The Web Conference/World Wide Web Conference

• Towards Societal Impact of AI
  C. Zhang
  [AAAI'23] The AAAI Conference on Artificial Intelligence (New Faculty Highlights)

• Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
  M. Ju, Y. Fan, C. Zhang, Y. Ye
  [AAAI'23] The AAAI Conference on Artificial Intelligence

• Heterogeneous Graph Masked Autoencoders
  Y. Tian, K. Dong, C. Zhang, C. Zhang, N. Chawla
  [AAAI'23] The AAAI Conference on Artificial Intelligence

• Boosting Graph Neural Networks via Adaptive Knowledge Distillation
  Z. Guo, C. Zhang, Y. Fan, Y. Tian, C. Zhang, N. Chawla
  [AAAI'23] The AAAI Conference on Artificial Intelligence

• Cross-domain Few-shot Graph Classification with a Reinforced Task Coordinator
  Q. Zhang, S. Pei, Q. Yang, C. Zhang, N. Chawla, X. Zhang
  [AAAI'23] The AAAI Conference on Artificial Intelligence

• Self-Supervised Graph Structure Refinement for Graph Neural Networks
  J. Zhao, Q. Wen, M. Ju, Y. Ye, C. Zhang
  [WSDM'23] The ACM International Conference on Web Search and Data Mining

• Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs
  Q. Yang, C. Ma, Q. Zhang, X. Gao, C. Zhang, X. Zhang
  [WSDM'23] The ACM International Conference on Web Search and Data Mining

2022

• Co-Modality Imbalanced Graph Contrastive Learning
  Y. Qian, C. Zhang, Y. Zhang, Q. Wen, Y. Ye, C. Zhang
  [NeurIPS'22] The Conference on Neural Information Processing Systems

• Label-invariant Augmentation for Semi-Supervised Graph Classification
  H. Yue, C. Zhang, C. Zhang, H. Liu
  [NeurIPS'22] The Conference on Neural Information Processing Systems

• Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering
  M. Ju, W. Yu, T. Zhao, C. Zhang, Y. Ye
  [EMNLP'22] The Conference on Empirical Methods in Natural Language Processing (Findings)

• GraphBERT: Bridging Graph and Text for Malicious Behavior Detection on Social Media
  J. Wu, C. Zhang, Z. Liu, E. Zhang, S. Wilson, C. Zhang
  [ICDM'22] The IEEE International Conference on Data Mining

• Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation
  C. Zhang, C. Huang, Y. Li, X. Zhang, Y. Ye, C. Zhang
  [CIKM'22] The ACM International Conference on Information and Knowledge Management

• Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning
  Y. Qian, Y. Zhang, Y. Ye, C. Zhang
  [CIKM'22] The ACM International Conference on Information and Knowledge Management

• A Biased Sampling Method for Imbalanced Personalized Ranking
  L. Yu, S. Pei, F. Zhu, L. Li, J. Zhou, C. Zhang, X. Zhang
  [CIKM'22] The ACM International Conference on Information and Knowledge Management

• Task-Adaptive Few-shot Node Classification
  S. Wang, K. Ding, C. Zhang, C. Chen, J. Li
  [KDD'22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction
  Q. Wen, Z. Ouyang, J. Zhang, Y. Qian, Y. Ye, C. Zhang
  [KDD'22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning
  Y. Qian, Y. Zhang, Q. Wen, Y. Ye, C. Zhang
  [KDD'22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer
  Q. Zhang, X. Wu, Q. Yang, C. Zhang, X. Zhang
  [KDD'22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Self-Augmented Hypergraph Transformer for Recommender Systems
  L. Xia, C. Huang, C. Zhang
  [KDD'22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Few-Shot Learning on Graphs
  C. Zhang, K. Ding, J. Li, X. Zhang, Y. Ye, N. Chawla, H. Liu
  [IJCAI'22] The International Joint Conference on Artificial Intelligence

• Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
  Y. Tian, C. Zhang, Z. Guo, Y. Ma, R. Metoyer, N. Chawla
  [IJCAI'22] The International Joint Conference on Artificial Intelligence

• RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation
  Y. Tian, C. Zhang, Z. Guo, C. Huang, R. Metoyer, N. Chawla
  [IJCAI'22] The International Joint Conference on Artificial Intelligence

• Rx-refill Graph Neural Network to Reduce Drug Overprescribing Risks
  J. Zhang, A. Kuo, J. Zhao, Q. Wen, E. Winstanley, C. Zhang, Y. Ye
  [IJCAI'22] The International Joint Conference on Artificial Intelligence (Best Paper Track)

• Adapting Distilled Knowledge for Few-shot Relation Reasoning over Knowledge Graphs
  Y. Zhang, Y. Qian, Y. Ye, C. Zhang
  [SDM'22] The SIAM International Conference on Data Mining

• Heterogeneous Temporal Graph Neural Network
  Y. Fan, M. Ju, C. Zhang, Y. Ye
  [SDM'22] The SIAM International Conference on Data Mining

• Graph Meta-learning over Heterogeneous Graphs
  Q. Zhang, X. Wu, Q. Yang, C. Zhang, X. Zhang
  [SDM'22] The SIAM International Conference on Data Mining

• Self-Augmented Graph Contrastive Learning
  L. Yu, S. Pei, L. Ding, J. Zhou, L. Long, C. Zhang, X. Zhang
  [AAAI'22] The AAAI Conference on Artificial Intelligence

• Interpretable Relation Learning on Heterogeneous Graphs
  Q. Yang, Q. Zhang, C. Zhang, X. Zhang
  [WSDM'22] The ACM International Conference on Web Search and Data Mining

2021

• Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media
  Y. Qian, Y. Zhang, Y. Ye, C. Zhang
  [NeurIPS'21] The Conference on Neural Information Processing Systems

• RxNet: Rx-refill Graph Neural Network for Overprescribing Detection
  J. Zhang, A. Kuo, J. Zhao, Q. Wen, E. Winstanley, C. Zhang, Y. Ye
  [CIKM'21] The ACM International Conference on Information and Knowledge Management
  Best Paper Award (1/1251)

• Recipe Representation Learning with Networks
  Y. Tian, C. Zhang, R. Metoyer, N. Chawla
  [CIKM'21] The ACM International Conference on Information and Knowledge Management

• Grounded Task Prioritization with Context-Aware Sequential Ranking
  C. Zhang, J. Kiseleva, S. Jauhar, R. White
  [TOIS] The ACM Transactions on Information Systems

• Inductive Contextual Relation Learning for Personalization
  C. Zhang, H. Yao, L. Yu, C. Huang, D. Song, H. Chen, M. Jiang, N. Chawla
  [TOIS] The ACM Transactions on Information Systems

• Multi-View Self-Supervised Heterogeneous Graph Embedding
  J. Zhao, Q. Wen, S. Sun, Y. Ye, C. Zhang
  [ECML/PKDD'21] The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

• Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection
  Y. Qian, Y. Zhang, Y. Ye, C. Zhang
  [IJCAI'21] The International Joint Conference on Artificial Intelligence

• Few-Shot Graph Learning for Molecular Property Prediction
  Z. Guo, C. Zhang, W. Yu, J. Herr, O. Wiest, M. Jiang, N. Chawla
  [WWW'21] The Web Conference/World Wide Web Conference

2020

• Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases
  C. Zhang, L. Yu, M. Saebi, M. Jiang, N. Chawla
  [EMNLP'20] The Conference on Empirical Methods in Natural Language Processing (Findings)

• GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction
  Z. Guo, W. Yu, C. Zhang, M. Jiang, N. Chawla
  [CIKM'20] The ACM International Conference on Information and Knowledge Management

• Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction
  C. Huang, C. Zhang, P. Dai, L. Bo
  [IJCAI'20] The International Joint Conference on Artificial Intelligence

• Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting
  X. Wu, C. Huang, C. Zhang, N. Chawla
  [WWW'20] The Web Conference/World Wide Web Conference

• Few-Shot Knowledge Graph Completion
  C. Zhang, H. Yao, C. Huang, M. Jiang, Z. Li, N. Chawla
  [AAAI'20] The AAAI Conference on Artificial Intelligence
  [code] [poster]

• Graph Few-Shot Learning via Knowledge Transfer
  H. Yao, C. Zhang, Y. Wei, M. Jiang, S. Wang, J. Huang, N. Chawla, Z. Li
  [AAAI'20] The AAAI Conference on Artificial Intelligence
  Short Version in The NeurIPS 2019 Graph Representation Learning Workshop

• Learning from Heterogeneous Networks: Methods and Applications
  C. Zhang
  [WSDM'20] The ACM International Conference on Web Search and Data Mining (Doctoral Consortium)

2019

• Heterogeneous Graph Neural Network
  C. Zhang, D. Song, C. Huang, A. Swami, N. Chawla
  [KDD'19] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  [code] [poster] [video]
  Most Influential Papers of KDD by Google Scholar

• Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics
  C. Huang, X. Wu, X. Zhang, C. Zhang, J. Zhao, D. Yin, N. Chawla
  [KDD'19] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting
  C. Huang, C. Zhang, J. Zhao, X. Wu, D. Yin, N. Chawla
  [WWW'19] The Web Conference/World Wide Web Conference
  Best Paper Award Candidate

• Deep Dynamic Fusion Network for Traffic Accident Forecasting
  C. Huang, C. Zhang, P. Dai, L. Bo
  [CIKM'19] The ACM International Conference on Information and Knowledge Management

• SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks
  C. Zhang, A. Swami, N. Chawla
  [WSDM'19] The ACM International Conference on Web Search and Data Mining
  [code] [slides]

• A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
  C. Zhang, D. Song, Y. Chen, X. Feng, C. Lumezanu, W. Cheng, J. Ni, B. Zong, H. Chen, N. Chawla
  [AAAI'19] The AAAI Conference on Artificial Intelligence
  [code upon request] [slides] [poster]
  Most Influential Papers of AAAI by Google Scholar

• Multi-order Attentive Ranking Model for Sequential Recommendation
  L. Yu, C. Zhang, S. Liang, X. Zhang
  [AAAI'19] The AAAI Conference on Artificial Intelligence

2018

• Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference
  C. Zhang, L. Yu, X. Zhang, N. Chawla
  [IJCAI'18] The International Joint Conference on Artificial Intelligence
  [code] [slides]

• Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification
  C. Zhang, C. Huang, L. Yu, X. Zhang, N. Chawla
  [WWW'18] The Web Conference/World Wide Web Conference
  [code] [slides]

• WalkRanker: A Unified Pairwise Ranking Model with Multiple Relations for Item Recommendation
  L. Yu, C. Zhang, S. Pei, G. Sun, X. Zhang
  [AAAI'18] The AAAI Conference on Artificial Intelligence

2017

• Collaborative User Network Embedding for Social Recommender Systems
  C. Zhang, L. Yu, Y. Wang, C. Shah, X. Zhang
  [SDM'17] The SIAM International Conference on Data Mining
  [code] [slides] [poster]
  Most Influential Papers of SDM by Google Scholar

• ImWalkMF: Joint Matrix Factorization and Implicit Walk Integrative Learning for Recommendation
  C. Zhang, L. Yu, X. Zhang, N. Chawla
  [BigData'17] The IEEE International Conference on Big Data

Earlier Papers

• A Community-aware Approach to Minimizing Dissemination in Graphs
  C. Zhang, L. Yu, C. Liu, Z.K. Zhang, T. Zhou
  [APWeb-WAIM'17] The APWeb-WAIM Joint International Conference on Web and Big Data

• AdaWIRL: A Novel Bayesian Ranking Approach for Personal Big-Hit Paper Prediction
  C. Zhang, L. Yu, J. LU, T. Zhou, Z.K. Zhang
  [APWeb-WAIM'16] The APWeb-WAIM Joint International Conference on Web and Big Data

• Rankmbpr: Rank-aware Mutual Bayesian Personalized Ranking for Item Recommendation
  L. Yu, G. Zhou, C. Zhang, J. Huang, C. Liu, Z.K. Zhang
  [APWeb-WAIM'16] The APWeb-WAIM Joint International Conference on Web and Big Data
  Best Student Paper Award (1/249)

• Dynamics of Information Diffusion and Its Applications on Complex Networks
  Z.K. Zhang, C. Liu, X.X. Zhan, X. LU, C.X. Zhang, Y.C. Zhang
  Physics Reports, 651:1-34, 2016

• Emergence of Blind Areas in Information Spreading
  C.X. Zhang, Z.K. Zhang, X. Han, C. Liu
  PLOS ONE, 9(4): e95785, 2014

• Epidemic Spreading on Weighted Complex Networks
  Y. Sun, C. Liu, C.X. Zhang, Z.K. Zhang
  Physics Letters A, 378: 635-640, 2014

• Information Filtering via Collaborative User Clustering Modeling
  C.X. Zhang, Z.K. Zhang, L. Yu, C. Liu, H. Liu, X. Yan
  Physica A, 396:195-203, 2014

• An Evolving Model of Online Bipartite Networks
  C.X. Zhang, Z.K. Zhang, C. Liu
  Physica A, 392:6100-6106, 2013