Selected Publications:

• Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing [paper] [arXiv]

  Qiang Liu, Junfei Wu, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted

  
  

• Bi-Level Graph Structure Learning for Next POI Recommendation [paper]

  Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted

  
  

• Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks [paper] [arXiv] [code]

  Junfei Wu, Weizhi Xu, Qiang Liu (corresponding author), Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted

  
  

• Modality-Balanced Learning for Multimedia Recommendation [arXiv]

  Jinghao Zhang, Guofan Liu, Qiang Liu (corresponding author), Shu Wu and Liang Wang

  ACM International Conference on Multimedia (MM), 2024

  
  

• DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization [paper] [arXiv]

  Xin Sun, Liang Wang, Qiang Liu (corresponding author), Shu Wu, Zilei Wang and Liang Wang

  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

  
  

• Rethinking Fair Graph Neural Networks from Re-balancing [paper] [arXiv] [code]

  Zhixun Li, Yushun Dong, Qiang Liu and Jeffrey Xu Yu

  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

  
  

• Stealthy Attack on Large Language Model based Recommendation [paper] [arXiv] [code]

  Jinghao Zhang, Yuting Liu, Qiang Liu, Shu Wu, Guibing Guo and Liang Wang

  Annual Meeting of the Association for Computational Linguistics (ACL), 2024

  
  

• Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models [paper] [arXiv] [code]

  Junfei Wu, Qiang Liu, Ding Wang, Jinghao Zhang, Shu Wu, Liang Wang and Tieniu Tan

  Annual Meeting of the Association for Computational Linguistics Findings (ACL Findings), 2024

  
  

• Chain-of-History Reasoning for Temporal Knowledge Graph Forecasting [paper] [arXiv]

  Yuwei Xia, Ding Wang, Qiang Liu (corresponding author), Liang Wang, Shu Wu and Xiao-Yu Zhang

  Annual Meeting of the Association for Computational Linguistics Findings (ACL Findings), 2024

  
  

• Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection [paper] [arXiv]

  Xiang Tao, Liang Wang, Qiang Liu (corresponding author), Shu Wu and Liang Wang

  The Web Conference (WWW), 2024

  
  

• CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction [paper]

  Liang Wang, Hao Fu, Shu Wu, Qiang Liu (corresponding author), Xuelei Tan, Fangsheng Huang, Mengdi Zhang and Wei Wu

  SIAM Conference on Data Mining (SDM), 2024

  
  

• Stage-Aware Hierarchical Attentive Relational Network for Diagnosis Prediction [paper]

  Liping Wang, Qiang Liu, Mengqi Zhang, Yaxuan Hu, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024

  
  

• Rethinking Graph Masked Autoencoders through Alignment and Uniformity [paper] [arXiv] [code]

  Liang Wang, Xiang Tao, Qiang Liu, Shu Wu and Liang Wang

  AAAI Conference on Artificial Intelligence (AAAI), 2024

  
  

• Text-Guided Molecule Generation with Diffusion Language Model [paper] [arXiv] [code]

  Haisong Gong, Qiang Liu, Shu Wu and Liang Wang

  AAAI Conference on Artificial Intelligence (AAAI), 2024

  
  

• Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables [paper] [arXiv]

  Haisong Gong, Weizhi Xu, Shu Wu, Qiang Liu and Liang Wang

  AAAI Conference on Artificial Intelligence (AAAI), 2024

  
  

• GSLB: The Graph Structure Learning Benchmark [paper] [arXiv] [code]

  Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu (corresponding author), Shu Wu, Liang Wang and Jeffrey Xu Yu

  Advances in Neural Information Processing Systems (NeurIPS), 2023

  
  

• Uncovering Neural Scaling Law in Molecular Representation Learning [paper] [arXiv] [code]

  Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu and Liang Wang

  Advances in Neural Information Processing Systems (NeurIPS), 2023

  
  

• Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation [paper] [arXiv] [code]

  Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023

  
  

• Noise-Robust Semi-Supervised Learning for Distantly Supervised Relation Extraction [paper]

  Xin Sun, Qiang Liu (corresponding author), Shu Wu, Zilei Wang and Liang Wang

  Conference on Empirical Methods in Natural Language Processing Findings (EMNLP Findings), 2023

  
  

• Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations [paper] [arXiv]

  Qiang Liu (co-first and corresponding author), Yingtao Luo, Yuntian Chen, Wenbo Hu, Tian Tian and Jun Zhu

  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023

  
  

• DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design [paper] [arXiv] [code]

  Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang and Quanquan Gu

  International Conference on Machine Learning (ICML), 2023

  
  

• Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation [paper] [arXiv]

  Jinghao Zhang, Qiang Liu, Shu Wu and Liang Wang

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2023

  
  

• Counterfactual Debiasing for Fact Verification [paper]

  Qiang Liu (co-first author), Weizhi Xu, Shu Wu and Liang Wang

  Annual Meeting of the Association for Computational Linguistics (ACL), 2023

  
  

• Learning Latent Relations for Temporal Knowledge Graph Reasoning [paper]

  Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu and Liang Wang

  Annual Meeting of the Association for Computational Linguistics (ACL), 2023

  
  

• RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring [paper] [arXiv]

  Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023

  
  

• Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning [paper] [code]

  Mengqi Zhang, Yuwei Xia, Qiang Liu (corresponding author), Shu Wu and Liang Wang

  The Web Conference (WWW), 2023

  
  

• Dynamic Graph Neural Networks for Sequential Recommendation [paper] [arXiv] [code]

  Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023

  
  

• MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning [paper] [arXiv]

  Yuwei Xia, Mengqi Zhang, Qiang Liu (corresponding author), Shu Wu and Xiao-Yu Zhang

  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022

  
  

• Deep Stable Representation Learning on Electronic Health Records [paper] [arXiv] [code]

  Yingtao Luo, Zhaocheng Liu and Qiang Liu (corresponding author)

  IEEE International Conference on Data Mining (ICDM), 2022

  
  

• The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection [paper] [arXiv]

  Zhixun Li, Dingshuo Chen, Qiang Liu and Shu Wu

  IEEE International Conference on Data Mining (ICDM), 2022

  
  

• GraphDIVE: Graph Classification by Mixture of Diverse Experts [paper] [arXiv]

  Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  International Joint Conference on Artificial Intelligence (IJCAI), 2022

  
  

• Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention [paper] [code]

  Junfei Wu, Qiang Liu, Weizhi Xu and Shu Wu

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2022

  
  

• Structure-Enhanced Heterogeneous Graph Contrastive Learning [paper]

  Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

  SIAM International Conference on Data Mining (SDM), 2022

  
  

• Evidence-aware Fake News Detection with Graph Neural Networks [paper] [arXiv] [code]

  Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu and Liang Wang

  The Web Conference (WWW), 2022

  
  

• An Empirical Study of Graph Contrastive Learning [paper] [arXiv] [code]

  Yanqiao Zhu, Yichen Xu, Qiang Liu and Shu Wu

  Advances in Neural Information Processing Systems (NeurIPS), 2021

  
  

• Mining Cross Features for Financial Credit Risk Assessment [paper] [arXiv]

  Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen and Jun Zhu

  ACM International Conference on Information and Knowledge Management (CIKM), 2021

  
  

• Mining Latent Structures for Multimedia Recommendation [paper] [arXiv] [code]

  Jinghao Zhang, Yanqiao Zhu, Qiang Liu (corresponding author), Shu Wu, Shuhui Wang and Liang Wang

  ACM International Conference on Multimedia (MM), 2021

  
  

• STAN: Spatio-Temporal Attention Network for Next Location Recommendation [paper] [arXiv] [code]

  Yingtao Luo, Qiang Liu (corresponding author) and Zhaocheng Liu

  The Web Conference (WWW), 2021

  
  

• Graph Contrastive Learning with Adaptive Augmentation [paper] [arXiv] [code]

  Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu and Liang Wang

  The Web Conference (WWW), 2021

  
  

• MV-RNN: A Multi-view Recurrent Neural Network for Sequential Recommendation [paper] [arXiv] [code]

  Qiang Cui, Shu Wu, Qiang Liu, Wen Zhong and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020

  
  

• Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-Based Feature Extractor [paper]

  Jingyi Wang, Qiang Liu, Zhaocheng Liu and Shu Wu

  ACM International Conference on Information and Knowledge Management (CIKM), 2019

  
  

• Mining Significant Microblogs for Misinformation Identification: An Attention-based Approach [paper]

  Qiang Liu, Feng Yu, Shu Wu and Liang Wang

  ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2018

  
  

• A Convolutional Approach for Misinformation Identification [paper]

  Feng Yu, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  International Joint Conference on Artificial Intelligence (IJCAI), 2017

  
  

• DeepStyle: Learning User Preferences for Visual Recommendation [paper]

  Qiang Liu, Shu Wu and Liang Wang

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2017

  
  

• Multi-behavioral Sequential Prediction with Recurrent Log-bilinear Model [paper]

  Qiang Liu, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2017

  
  

• Context-aware Sequential Recommendation [paper]

  Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li and Liang Wang

  IEEE International Conference on Data Mining (ICDM), 2016

  
  

• Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts [paper]

  Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  AAAI Conference on Artificial Intelligence (AAAI), 2016

  
  

• A Dynamic Recurrent Model for Next Basket Recommendation [paper]

  Qiang Liu (co-first author), Feng Yu, Shu Wu, Liang Wang and Tieniu Tan

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2016

  
  

• Contextual Operation for Recommender Systems [paper]

  Shu Wu, Qiang Liu, Liang Wang and Tieniu Tan

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2016

  
  

• Collaborative Prediction for Multi-entity Interaction with Hierarchical Representation [paper]

  Qiang Liu, Shu Wu and Liang Wang

  ACM International Conference on Information and Knowledge Management (CIKM), 2015

  
  

• COT: Contextual Operating Tensor for Context-aware Recommender Systems [paper]

  Qiang Liu, Shu Wu and Liang Wang

  AAAI Conference on Artificial Intelligence (AAAI), 2015