[1] Weibo Gao, Qi Liu*, Rui Li, Yuze Zhao, Hao Wang, Linan Yre, Fangzhou Yao, Zheng Zhang. Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor. KDD 2025: Accepted.
[2] Kefan Wang, Hao Wang*, Wei Guo, Jianghao Lin, Defu Lian, and Enhong Chen. DLF: Enhancing Explicit-Implicit Interaction via Dynamic Low-Order-Aware Fusion for CTR Prediction. SIGIR 2025: Accepted.
[3] Jiaqing Zhang, Mingjia Yin, Hao Wang*, Yawen Li, Yuyang Ye, Xingyu Lou, Junping Du, Enhong Chen*. TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation. WWW 2025: Accepted.
[4] Hao Wang*, Wei Guo, Luankang Zhang, Jin Yao Chin, Yufei Ye, Huifeng Guo, Yong Liu, Defu Lian, Ruiming Tang, Enhong Chen. Generative Large Recommendation Models: Emerging Trends in LLMs for Recommendation. WWW 2025: Accepted.
[5] Yufei Ye#, Wei Guo#, Jin Yao Chin, Hao Wang* , Hong Zhu, Xi Lin, Yuyang Ye, Yong Liu, Ruiming Tang*, Defu Lian*, Enhong Chen*. FuXi-alpha: Scaling Recommendation Model with Feature Interaction Enhanced Transformer. WWW 2025: Accepted.
[6] Rui Zhou, Hao Wang* , Wei Guo, Qinglin Jia, Wenjia Xie, Xiang Xu, Yong Liu, Defu Lian, Enhong Chen. MIT: A Multi-Tower Information Transfer Framework Based on Hierarchical Task Relationship Modeling. WWW 2025: Accepted.
[7] Kefan Wang, Hao Wang* , Kenan Song, Wei Guo, Kai Cheng, Zhi Li, Yong Liu, Defu Lian, Enhong Chen*. A Universal Framework for Compressing Embeddings in CTR Prediction. DASFAA 2025: Accepted.
[8] Xiang Xu, Hao Wang*, Wei Guo, Luankang Zhang, Wanshan Yang, Runlong Yu, Yong Liu, Defu Lian, Enhong Chen*. Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction. KDD 2025: Accepted.
[9] Weibo Gao, Qi Liu*, Linan Yue, Fangzhou Yao, Hao Wang, Yin Gu, Zheng Zhang. Collaborative cognitive diagnosis with disentangled representation learning for learner modeling. NeurIPS 2024: Accepted.
[10] Wenjia Xie, Hao Wang* , Luankang Zhang, Rui Zhou, Defu Lian, Enhong Chen. Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model. NeurIPS 2024: Accepted.
[11] Mingjia Yin, Hao Wang* , Wei Guo, Yong Liu, Suojuan Zhang, Sirui Zhao, Defu Lian, Enhong Chen. Dataset Regeneration for Sequential Recommendation. KDD 2024 Best Student Paper Award: Accepted.
[12] Mingjia Yin, Hao Wang*, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen. APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. CIKM 2023: Accepted.
[13] Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang*, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu*, Qi Liu, Hui Xiong*, Enhong Chen. A Survey on Large Language Models for Recommendation. ArXiv 2023: Submission.
[14] Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Yuting Ning, Jianhui Ma, Qi Liu, Enhong Chen*. TechPat: Technical Phrase Extraction for Patent Mining. TKDD 2023: Accepted.
[15] Likang Wu, Junji Jiang, Hongke Zhao, Hao Wang*, Defu Lian, Mengdi Zhang, Enhong Chen. KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification. IJCAI 2023: Accepted.
[16] Weihao Zhao, Han Wu, Weidong He, Haoyang Bi, Hao Wang, Chen Zhu, Tong Xu, Enhong Chen. Hierarchical Multi-modal Attention Network for Time-sync Comment Video Recommendation. TCSVT 2023: Accepted.
[17] Han Wu, Guanqi Zhu, Qi Liu, Hengshu Zhu, Hao Wang, Hongke Zhao, Chuanren Liu, Enhong Chen, Hui Xiong. A Multi-Aspect Neural Tensor Factorization Framework for Patent Litigation Prediction. TBD 2023: Accepted.
[18] Weibo Gao, Hao Wang, Qi Liu*, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang. Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis. SIGIR 2023: Accepted.
[19] Zepu Lu, Defu Lian, Jin Zhang, Zaixi Zhang, Chao Feng, Hao Wang, Enhong Chen. Differentiable Optimized Product Quantization and Beyond. WWW 2023: Accepted.
[20] Yongqiang Han, Likang Wu, Hao Wang*, Guifeng Wang, Mengdi Zhang, Zhi Li, Defu Lian, Enhong Chen. GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation. DASFAA 2023: Accepted.
[21] Sirui Zhao, Huaying Tang, Xinglong Mao, Shifeng Liu, Hanqing Tao, Hao Wang, Tong Xu, Enhong Chen. More is Better: A Database for Spontaneous Micro-Expression with High Frame Rates. ArXiv 2023: Submission.
[22] Liyang He, Zhenya Huang*, Enhong Chen, Qi Liu, Shiwei Tong, Hao Wang , Defu Lian, Shijin Wang. An Efficient and Robust Semantic Hashing Framework for Similar Text Search. TOIS 2023: Accepted.
[23] Hang Zhang, Hao Wang* , Guifeng Wang, Jiayu Liu, Qi Liu. A Hyperbolic-to-Hyperbolic User Representation with Multi-aspect for Social Recommendation. CIKM 2022: 4667-4671.
[24] Wenhao Leng, Sirui Zhao, Yiming Zhang, Shiifeng Liu, Xinglong Mao, Hao Wang , Tong Xu, Enhong Chen. ABPN: Apex and Boundary Perception Network for Micro-and Macro-Expression Spotting. MM 2022: 7160-7164.
[25] Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang , Chee-Kong Lee, Enhong Chen. Model inversion attacks against graph neural networks. TKDE 2022: Accepted.
[26] Qi Liu, Jinze Wu, Zhenya Huang, Hao Wang , Yuting Ning, Ming Chen, Enhong Chen, Jinfeng Yi, Bowen Zhou. Federated User Modeling from Hierarchical Information. TOIS 2022: Accepted.
[27] Wei Cao, Kun Zhang, Shulan Ruan, Hanqing Tao, Sirui Zhao, Hao Wang , Qi Liu, Enhong Chen. MCausal Narrative Comprehension: A New Perspective for Emotion Cause Extraction. TAFFC 2022: 1743-1758.
[28] Sirui Zhao, Huaying Tang, Shifeng Liu, Yangsong Zhang, Hao Wang , Tong Xu, Enhong Chen, Cuntai Guan. ME-PLAN: A deep prototypical learning with local attention network for dynamic micro-expression recognition. NN 2022: 427-443.
[29] Yanmin Chen, Hao Wang , Ruijun Sun, Enhong Chen. Context-Aware Semantic Matching with Self Attention Mechanism. PRAI 2022: 007-1011.
[30] Yuren Zhang, Enhong Chen*, Binbin Jin, Hao Wang , Min Hou, Wei Huang, Runlong Yu. Clustering based behavior sampling with long sequential data for CTR prediction. SIGIR 2022: 2195-2200.
[31] Likang Wu, Hao Wang* , Enhong Chen, Zhi Li, Hongke Zhao, Jianhui Ma. Preference Enhanced Social Influence Modeling for Network-Aware Cascade Prediction. SIGIR 2022: 2704-2708.
[32] Zaixi Zhang, Qi Liu, Hao Wang , Chengqiang Lu, Chee-Kong Lee. Protgnn: Towards self-explaining graph neural networks. AAAI 2022: 9127-9135.
[33] Shiwei Wu, Weidong He, Tong Xu, Hao Wang, Enhong Chen. Winning the CVPR’2022 AQTC Challenge: A Two-stage Function-centric Approach. CVPR AQTC Challenge 2022: None.
[34] Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang , Chengqiang Lu, Chee-Kong Lee. Motif-based graph self-supervised learning for molecular property prediction. NeurIPS 2021: None.
[35] Zhenya Huang, Xin Lin, Hao Wang , Qi Liu, Enhong Chen, Jianhui Ma, Yu Su, Wei Tong. Disenqnet: Disentangled representation learning for educational questions. KDD 2021: 696-704.
[36] Hao Wang , Defu Lian, Hanghang Tong, Qi Liu, Zhenya Huang, Enhong Chen. Decoupled Representation Learning for Attributed Networks. TKDE 2021: Accepted.
[37] Hao Wang , Defu Lian, Hanghang Tong, Qi Liu, Zhenya Huang, Enhong Chen*. HyperSoRec: Exploiting Hyperbolic User and Item Representations with Multiple Aspects for Social-aware Recommendation. TOIS 2021: Vol. 1, No. 1, Article 1.
[38] Gangwei Jiang, Hao Wang , Jin Chen, Haoyu Wang, Defu Lian*, Enhong Chen. xLightFM: Extremely Memory-Efficient Factorization Machine. SIGIR 2021: Accepted.
[39] Jinze Wu, Qi Liu, Zhenya Huang, Yuting Ning, Hao Wang , Enhong Chen, Jinfeng Yi, Bowen Zhou. Hierarchical Personalized Federated Learning for User Modeling. WWW 2021: Accepted.
[40] Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang , Chengqiang Lu, Chuanren Liu, Enhong Chen. GraphMI: Extracting Private Graph Data from Graph Neural Networks. IJCAI 2021: 3749-3755.
[41] Xin Lin, Zhenya Huang, Hongke Zhao, Enhong Chen, Qi Liu, Hao Wang , Shijin Wang. HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem. AAAI 2021: Accepted.
[42] Jinze Wu, Zhenya Huang, Qi Liu, Defu Lian, Hao Wang , Enhong Chen, Haiping Ma, Shijin Wang. Federated Deep Knowledge Tracing. WSDM 2021: Accepted.
[43] Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang , Zheyuan Hu, Qi Liu, Enhong Chen, Chee-Kong Lee. ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. KDD 2020: 731-739.
[44] Zhenya Huang, Qi Liu, Weibo Gao, Jinze Wu, Yu Yin, Hao Wang , Enhong Chen. Neural Mathematical Solver with Enhanced Formula Structure. SIGIR 2020: 1729-1732.
[45] Yanmin Chen, Hao Wang , Jianhui Ma, Dongfang Du, Hongke Zhao. A Hierarchical Attention Mechanism Framework for Internet Credit Evaluation. Journal of Computer Research and Development 2020: 57(8): 1755-1768.
[46] Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Jianhui Ma, Qi Liu, Enhong Chen, Hanqing Tao, Ke Rui. Technical Phrase Extraction for Patent Mining: A Multi-level Approach. ICDM 2020: 1142-1147.
[47] Binglei Wang, Tong Xu, Hao Wang , Yanmin Chen, Le Zhang, Lintao Fang, Guiquan Liu, Enhong Chen. Author Contributed Representation for Scholarly Network. APWeb-WAIM 2020: 558-573.
[48] Hao Wang , Tong Xu, Qi Liu, Defu Lian, Enhong Chen, Dongfang Du, Han Wu, Wen Su. MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network. KDD 2019: 1064-1072.
[49] Hao Wang , Enhong Chen*, Qi Liu, Tong Xu, Dongfang Du, Wen Su, Xiaopeng Zhang. A united approach to learning sparse attributed network embedding. ICDM 2018: Accepted.
[50] Hongjie Lin, Hao Wang , Dongfang Du, Han Wu, Biao Chang, Enhong Chen*. Patent Quality Valuation with Deep Learning Models. DASFAA 2018: 474-490.
[51] Dongfang Du, Hao Wang , Tong Xu, Yanan Lu, Qi Liu, Enhong Chen. Solving link-oriented tasks in signed network via an embedding approach. SMC 2017: Accepted.