Publications

(* means the corresponding author.)

Journal Papers

• Explainable Session-based Recommendation via Path Reasoning
  Yang Cao, Shuo Shang*, Jun Wang, and Wei Zhang*
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2024.
  

• Modeling Dynamic Item Tendency Bias in Sequential Recommendation with Causal Intervention
  Zihan Liao, Xiaodong Wu, Shuo Shang, Jun Wang, and Wei Zhang*
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2024.
  

• Improving the Performance and Explainability of Knowledge Tracing via Markov Blanket
  Bo Jiang, Yuang Wei, Ting Zhang, and Wei Zhang
  Information Processing & Management (IPM) (Full Paper), 2024.
  

• Understanding Adversarial Robustness From Feature Maps of Convolutional Layers
  Cong Xu, Wei Zhang, Jun Wang, and Min Yang
  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) (Full Paper), 2024.
  

• Learning Interpretable Rules for Scalable Data Representation and Classification
  Zhuo Wang, Wei Zhang*, Ning Liu, and Jianyong Wang*
  IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) (Regular Paper), 2023.
  

• Contrastive Personalized Exercise Recommendation with Reinforcement Learning
  Siyu Wu, Jun Wang, and Wei Zhang*
  IEEE Transactions on Learning Technologies (IEEE TLT) (Regular Paper), 2023.
  

• StableGCN: Decoupling and Reconciling Information Propagation for Collaborative Filtering
  Cong Xu, Jun Wang*, and Wei Zhang*
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2023.
  

• Knowledge-aware Collaborative Filtering with Pre-trained Language Model for Personalized Review-based Rating Prediction
  Quanxiu Wang, Xinlei Cao, Jianyong Wang, and Wei Zhang*
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2023.
  

• Conditional Pseudo-supervised Contrast for Data-Free Knowledge Distillation
  Renrong Shao, Wei Zhang*, and Jun Wang
  Pattern Recognition (PR) (Full Paper), 2023.
  

• Fine-Grained Interaction Modeling with Multi-Relational Transformer for Knowledge Tracing
  Jiajun Cui, Zeyuan Chen, Aimin Zhou, Jianyong Wang, and Wei Zhang*
  ACM Transactions on Information Systems (ACM TOIS) (Full Paper), 2023.
  

• Contrastive Author-aware Text Clustering
  Xudong Tang, Chao Dong, and Wei Zhang*
  Pattern Recognition (PR) (Full Paper), 2022.
  

• A KG-enhanced Multi-Graph Neural Network for Attentive Herb Recommendation
  Yuanyuan Jin, Wendi Ji, Wei Zhang, Xiangnan He, Xinyu Wang, and Xiaoling Wang
  IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE/ACM TCBB) (Regular Paper), 2021.
  

• Hierarchical Multi-Agent Reinforcement Learning for Allocating Guaranteed Display Ads
  Lu Wang, Lei Han, Xinru Chen, Chengchang Li, Junzhou Huang, Weinan Zhang, Wei Zhang*, Xiaofeng He*, Dijun Luo
  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) (Full Paper), 2021.
  

• Incorporating Link Prediction into Multi-Relational Item Graph Modeling for Session-based Recommendation
  Wen Wang, Wei Zhang*, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, Hongyuan Zha
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2021.
  

• Learning from Substitutable and Complementary Relations for Graph-based Sequential Product Recommendation
  Wei Zhang, Zeyuan Chen, Hongyuan Zha, Jianyong Wang
  ACM Transactions on Information Systems (ACM TOIS) (Full Paper), 2021.
  

• Attentive Representation Learning with Adversarial Training for Short Text Clustering
  Wei Zhang, Chao Dong, Jianhua Yin, Jianyong Wang
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2021.
  

• Learning Social Relations and Spatiotemporal Trajectories for Next Check-in Inference
  Wenwei Liang, Wei Zhang*
  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) (Full Paper), 2020.
  

• Social Link Inference via Multiview Matching Network From Spatiotemporal Trajectories
  Wei Zhang, Xin Lai, Jianyong Wang
  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) (Full Paper), 2020.
  

• Adaptive Multi-Teacher Multi-level Knowledge Distillation
  Yuang Liu, Wei Zhang*, Jun Wang*
  Neurocomputing, 2020.
  

• Integrating Topic and Latent Factors for Scalable Personalized Review-based Rating Prediction
  Wei Zhang, Jianyong Wang
  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) (Regular Paper), 2016.
  

Conference Papers

• Exploring Feature-based Knowledge Distillation For Recommender System: A Frequency Perspective
  Zhangchi Zhu and Wei Zhang*
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
  

• Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
  Cong Xu, Jun Wang, Jianyong Wang, and Wei Zhang*
  Advances in Neural Information Processing Systems (NeurIPS), 2024.
  

• Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing
  Jiajun Cui, Hong Qian, Bo Jiang, and Wei Zhang*
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
  

• Capturing Homogeneous Influence among Students: Hypergraph Cognitive Diagnosis for Intelligent Education Systems
  Junhao Shen, Hong Qian, Shuo Liu, Wei Zhang, Bo Jiang, and Aimin Zhou
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
  

• D2LLM: Decomposed and Distilled Large Language Models for Semantic Search
  Zihan Liao, Hang Yu, Jianguo Li*, Jun Wang*, and Wei Zhang*
  Annual Meeting of the Association for Computational Linguistics (ACL) (Oral: about 3%),, 2024.
  

• Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
  Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang
  Annual Meeting of the Association for Computational Linguistics (Findings of ACL), 2024.
  

• Interpretable Knowledge Tracing via Response Influence-based Counterfactual Reasoning
  Jiajun Cui, Minghe Yu, Bo Jiang, Aimin Zhou, Jianyong Wang, and Wei Zhang*
  IEEE International Conference on Data Engineering (ICDE), 2024.
  

• Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systems
  Junhao Shen, Hong Qian, Wei Zhang, and Aimin Zhou
  AAAI Conference on Artificial Intelligence (AAAI), 2024.
  

• DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting
  Ruixin Ding, Yuqi Chen, Yuting Lan, and Wei Zhang*
  ACM International Conference on Information and Knowledge Management (CIKM), 2024.
  

• TRELM: Towards Robust and Efficient Pre-training for Knowledge-Enhanced Language Models
  Junbing Yan, Chengyu Wang*, Taolin Zhang, Xiaofeng He, Jun Huang, Longtao Huang, Hui Xue, and Wei Zhang*
  International Conference on Computational Linguistics (COLING), 2024.
  

• DMT: Comprehensive Distillation with Multiple Self-supervised Teachers
  Yuang Liu, Jing Wang, Qiang Zhou, Fan Wang, Jun Wang, and Wei Zhang*
  International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.
  

• Dynamic Token-Pass Transformers for Semantic Segmentation
  Yuang Liu, Qiang Zhou, Jing Wang, Fan Wang, Jun Wang, and Wei Zhang*
  IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.
  

• Learning to Binarize Continuous Features for Neuro-Rule Networks
  Wei Zhang, Yongxiang Liu, Zhuo Wang, and Jianyong Wang
  International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  

• Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction
  Zhangchi Zhu, Lu Wang, Pu Zhao, Chao Du, Wei Zhang*, Hang Dong, Bo Qiao, Qingwei Lin*, Saravan Rajmohan, and Dongmei Zhang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.
  

• Quantize Sequential Recommenders Without Private Data
  Lingfeng Shi, Yuang Liu, Jun Wang, and Wei Zhang*
  The Web conference (WWW), 2023.
  

• Data-free Knowledge Distillation for Fine-grained Vision Categorization
  Renrong Shao, Wei Zhang*, Jianhua Yin, and Jun Wang*
  International Conference on Computer Vision (ICCV), 2023.
  

• Self-Decoupling and Ensemble Distillation for Efficient Segmentation
  Yuang Liu, Wei Zhang*, and Jun Wang*
  AAAI Conference on Artificial Intelligence (AAAI), 2023.
  

• From Complex to Simple: Unraveling the Cognitive Tree for Reasoning with Small Language Models
  Junbing Yan, Chengyu Wang, Taolin Zhang, Xiaofeng He, Jun Huang and Wei Zhang*
  Empirical Methods in Natural Language Processing (Findings of EMNLP), 2023.
  

• Beyond Semantics: Learning a Behavior Augmented Relevance Model with Self-supervised Learning
  Zeyuan Chen, Wei Chen, Jia Xu, Zhongyi Liu, and Wei Zhang
  ACM International Conference on Information and Knowledge Management (CIKM), 2023.
  

• Neuro-Symbolic Interpretable Collaborative Filtering for Attribute-based Recommendation
  Wei Zhang, Junbing Yan, Zhuo Wang, and Jianyong Wang
  The Web conference (WWW), 2022.
  

• Multi-Knowledge Aggregation and Transfer for Semantic Segmentation
  Yuang Liu, Wei Zhang*, and Jun Wang*
  AAAI Conference on Artificial Intelligence (AAAI), 2022.
  

• Effective Few-Shot Named Entity Linking by Meta-Learning
  Xiuxing Li, Zhenyu Li, Zhengyan Zhang, Ning Liu, Haitao Yuan, Wei Zhang, Zhiyuan Liu, and Jianyong Wang
  IEEE International Conference on Data Engineering (ICDE), 2022.
  

• Is it fair? Resource allocation for differentiated services on demands
  Ran Zhang, Ning Liu, Lei Liu, Wei Zhang, Haitao Yuan, Mianxiong Dong, and Lizhen Cui
  IEEE International Conference on Web Services (ICWS) (Short Paper), 2022.
  

• Multi-view Pre-trained Model for Code Vulnerability Identification
  Xuxiang Jiang, Yinhao Xiao, Jun Wang, and Wei Zhang*
  International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2022.
  

• IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
  Pan Lu, Liang Qiu, Jiaqi Chen, Tony Xia, Yizhou Zhao, Wei Zhang, Zhou Yu, Xiaodan Liang, and Song-Chun Zhu
  Advances in Neural Information Processing Systems (NeurIPS) (Datasets and Benchmarks Track), 2021.
  

• Scalable Rule-Based Representation Learning for Interpretable Classification
  Zhuo Wang, Wei Zhang*, Ning Liu, and Jianyong Wang*
  Advances in Neural Information Processing Systems (NeurIPS), 2021.
  

• Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation
  Zeyuan Chen, Wei Zhang*, Junchi Yan, Gang Wang, Jianyong Wang
  ACM International Conference on Information and Knowledge Management (CIKM), 2021.
  

• Zero-shot Adversarial Quantization
  Yuang Liu, Wei Zhang*, Jun Wang*
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral: about 4%), 2021.
  

• Source-Free Domain Adaptation for Semantic Segmentation
  Yuang Liu, Wei Zhang*, Jun Wang*
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  

• Graph-Based Tri-Attention Network for Answer Ranking in CQA
  Wei Zhang, Zeyuan Chen, Chao Dong, Wen Wang, Hongyuan Zha, Jianyong Wang
  AAAI Conference on Artificial Intelligence (AAAI), 2021.
  

• Susceptible Temporal Patterns Discovery for Electronic Health Records via Adversarial Attack
  Rui Zhang, Wei Zhang, Ning Liu, Jianyong Wang
  International Conference on Database Systems for Advanced Applications (DASFAA), 2021.
  

• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation
  Wen Wang, Wei Zhang*, Jun Rao, Zhijie Qiu, Bo Zhang, Leyu Lin, Hongyuan Zha
  International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020.
  

• Syndrome-aware Herb Recommendation with Multi-Graph Convolution Network
  Yuanyuan Jing, Wei Zhang, Xiangnan He, Xinyu Wang, Xiaoling Wang
  IEEE International Conference on Data Engineering (ICDE), 2020.
  

• Beyond Clicks: Modeling Multi-Relational Item Graph for Session-based Target Behavior Prediction
  Wen Wang, Wei Zhang*, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, Hongyuan Zha
  The Web Conference (WWW) (Short Paper), 2020.
  

• Transparent Classification with Multilayer Logical Perceptrons and Random Binarization
  Zhuo Wang, Wei Zhang*, Ning Liu, Jianyong Wang*
  AAAI Conference on Artificial Intelligence (AAAI) ( Oral: about 5.9%), 2020.
  

• Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption
  Wei Zhang, Yue Ying, Pan Lu, Hongyuan Zha
  AAAI Conference on Artificial Intelligence (AAAI), 2020.
  

• Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning
  Qianming Xue, Wei Zhang*, Hongyuan Zha
  AAAI Conference on Artificial Intelligence (AAAI), 2020.
  

• HyFea: Winning Solution to Social Media Popularity Prediction for Multimedia Grand Challenge 2020
  Xin Lai, Yihong Zhang, Wei Zhang*
  ACM Multimedia Conference (MM) (Multimedia Grand Challenge), 2020.
  

• Sequential Multi-fusion Network for Multi-Channel Video CTR Prediction
  Wen Wang, Wei Zhang*, Wei Feng, Hongyuan Zha
  International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
  

• Improved Representations for Personalized Document-Level Sentiment Classification
  Yihong Zhang, Wei Zhang*
  International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
  

• Coupled Graph Neural Networks for Text-oriented Clinical Diagnosis Inference
  Ning Liu, Wei Zhang, Xiuxing Li, Haitao Yuan, Jianyong Wang
  International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
  

• Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model
  Yushun Dong, Yingxia Shao, Xiaotong Li, Sili Li, Lei Quan, Wei Zhang, Junping Du
  ACM International Conference on Information and Knowledge Management (CIKM), 2019.
  

• Learning Robust Representations with Graph Denoising Policy Network
  Lu Wang, Wenchao Yu, Wei Wang, Wei Cheng, Hongyuan Zha, Wei Zhang, Xiaofeng He, Haifeng Chen
  IEEE International Conference on Data Mining (ICDM) (Short Paper), 2019.
  

• Content-Based Video Relevance Prediction with Multi-View Multi-Level Deep Interest Network
  Zeyuan Chen, Kai Xu, Wei Zhang*
  ACM Multimedia Conference (MM) (Multimedia Grand Challenge), 2019.
  

• Knowledge-Aware Deep Dual Networks for Text-Based Mortality Prediction
  Ning Liu, Pan Lu, Wei Zhang*, Jianyong Wang
  IEEE International Conference on Data Engineering (ICDE), 2019.
  

• Continuous Patient-Centric Sequence Generation via Sequentially Coupled Adversarial Learning
  Lu Wang, Wei Zhang*, Xiaofeng He*
  International Conference on Database Systems for Advanced Applications (DASFAA), 2019.
  

• Deep Sequential Multi-Task Modeling for Next Check-in Time and Location Prediction
  Wenwei Liang, Wei Zhang*, Xiaoling Wang
  International Conference on Database Systems for Advanced Applications (DASFAA) (Short Paper), 2019.
  

• A Novel Hybrid Sequential Model for Review-Based Rating Prediction
  Yuanquan Lu, Wei Zhang*, Pan Lu, Jianyong Wang
  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019.
  

• Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation
  Lu Wang, Wei Zhang*, Xiaofeng He*, Hongyuan Zha
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.
  

• R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering
  Pan Lu, Lei Ji, Wei Zhang*, Nan Duan, Ming Zhou, Jianyong Wang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.
  

• Model-Based Clustering of Short Text Streams
  Jianhua Yin, Daren Chao, Zhongkun Liu, Wei Zhang*, Xiaohui Yu, Jianyong Wang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.
  

• User-Guided Hierarchical Attention Network for Multi-Modal Social Image Popularity Prediction
  Wei Zhang, Wen Wang, Jun Wang, Hongyuan Zha
  The Web Conference (WWW), 2018.
  

• Learning to Detect Pathogenic Microorganism of Community-Acquired Pneumonia
  Wenwei Liang, Wei Zhang*, Bo Jin, Jiangjiang Xu, Linhua Shu, Hongyuan Zha
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (Short Paper), 2018.
  

• Learning Sequential Correlation for User Generated Textual Content Popularity Prediction
  Wen Wang, Wei Zhang*, Jun Wang, Junchi Yan, Hongyuan Zha
  International Joint Conference on Artificial Intelligence (IJCAI), 2018.
  

• Co-Attending Free-Form Regions and Detections with Multi-Modal Multiplicative Feature Embedding for Visual Question Answering
  Pan Lu, Hongsheng Li, Wei Zhang, Jianyong Wang, Xiaogang Wang
  AAAI Conference on Artificial Intelligence (AAAI), 2018.
  

• Hybrid Deep Sequential Modeling for Social Text-Driven Stock Prediction
  Huizhe Wu, Wei Zhang*, Weiwei Shen, Jun Wang
  ACM International Conference on Information and Knowledge Management (CIKM) (Short Paper), 2018.
  

• Factorization Meets Memory Network: Learning to Predict Activity Popularity
  Wen Wang, Wei Zhang*, Jun Wang
  International Conference on Database Systems for Advanced Applications (DASFAA), 2018.
  

• Personalized Prescriptions for Comorbidity
  Lu Wang, Wei Zhang, Xiaofeng He, Hongyuan Zha
  International Conference on Database Systems for Advanced Applications (DASFAA), 2018.
  

• Combining Multiple Features for Image Popularity Prediction in Social Media
  Wen Wang, Wei Zhang*
  ACM Multimedia Conference (MM) (Multimedia Grand Challenge), 2017.
  

• Periodic Region Detection for Mobility Modeling of Social Media Users
  Quan Yuan, Wei Zhang, Chao Zhang, Xinhe Geng, Gao Cong, Jiawei Han
  ACM International Conference on Web Search and Data Mining (WSDM), 2017.
  

• Collaborative Multi-Level Embedding Learning from Reviews for Rating Prediction
  Wei Zhang, Quan Yuan, Jiawei Han, Jianyong Wang
  International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  

• Location and Time Aware Social Collaborative Retrieval for New Successive Point-of-Interest Recommendation
  Wei Zhang, Jianyong Wang
  ACM International Conference on Information and Knowledge Management (CIKM), 2015.
  

• A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation
  Wei Zhang, Jianyong Wang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015.
  

• Prior-based Dual Additive Latent Dirichlet Allocation for User-Item Connected Documents
  Wei Zhang, Jianyong Wang
  International Joint Conference on Artificial Intelligence (IJCAI), 2015.
  

• StreamCube: Hierarchical Spatio-Temporal Hashtag Clustering for Event Exploration over the Twitter Stream
  Wei Feng, Chao Zhang, Wei Zhang, Jiawei Han, Jianyong Wang, Charu Aggarwal, Jianbin Huang
  IEEE International Conference on Data Engineering (ICDE), 2015.
  

• Combining Latent factor Model with Location Features for Event-Based Group Recommendation
  Wei Zhang, Jianyong Wang, Wei Feng
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2013.
  

• Integrating Semantic Relatedness and Words’ Intrinsic Features for Keyword Extraction
  Wei Zhang, Wei Feng, Jianyong Wang
  International Joint Conference on Artificial Intelligence (IJCAI), 2013.
  

• Improving Noun Compounds Identification with Verb-Centered Dependency Relations
  Ruiji Fu, Wei Zhang, Bing Qin, Ting Liu
  Journal of Computational Information Systems (JCIS), 2011.
  

中文期刊论文

• 记忆与认知融合的个性化OJ习题推荐方法
  金天成, 窦亮, 肖春芸, 张伟, 周爱民
  计算机学报, 2022.
  

• 深度学习中的知识蒸馏研究综述
  邵仁荣, 刘宇昂, 张伟*, 王骏
  计算机学报, 2022.
  

• 带有时间辅助预测任务的会话式序列推荐
  陈聪, 张伟*, 王骏*
  计算机学报, 2021 (NDBC'2020 会议萨师煊优秀学生论文奖).
  

• 融合时空行为与社交关系的用户轨迹识别模型
  张伟*, 李扬, 张吉, 王建勇
  计算机学报, 2021.
  

• 目标依赖的作者身份识别方法
  李扬, 张伟*, 彭晨
  计算机应用, 2020 (NDBC'2019 会议论文报告).
  

• 基于层次注意力机制的多任务疾病进展模型
  潘祖江, 刘宁, 张伟*, 王建勇*
  计算机科学, 2020 (NDBC'2019 会议论文报告).
  

• 基于维基百科类别图的推特用户兴趣挖掘
  刘小捷, 吕晓强, 王晓玲, 张伟, 赵安
  计算机科学, 2019 (NDBC'2018 会议论文报告).