Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering. - Wenzheng Feng; Yu Wu 012; Wei Wu 014; Zhoujun Li 001; Ming Zhou 001 (SemEval@ACL, 2017)

Course Concept Extraction in MOOC via Explicit/Implicit Representation. - Xiaochen Wang 002; Wenzheng Feng; Jie Tang 001; Qingyang Zhong (DSC, 2018)

Understanding Dropouts in MOOCs. - Wenzheng Feng; Jie Tang 001; Tracy Xiao Liu (AAAI, 2019)

MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. - Jifan Yu; Gan Luo; Tong Xiao; Qingyang Zhong; Yuquan Wang; Wenzheng Feng; Junyi Luo; Chenyu Wang; Lei Hou 001; Juanzi Li; Zhiyuan Liu 001; Jie Tang 001 (ACL, 2020)

Graph Random Neural Networks for Semi-Supervised Learning on Graphs. - Wenzheng Feng; Jie Zhang 078; Yuxiao Dong; Yu Han 001; Huanbo Luan; Qian Xu 005; Qiang Yang 001; Evgeny Kharlamov; Jie Tang 001 (NeurIPS, 2020)

Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. - Jibing Gong; Shen Wang 005; Jinlong Wang 005; Wenzheng Feng; Hao Peng 001; Jie Tang 001; Philip S. Yu (SIGIR, 2020)

Graph Random Neural Network. - Wenzheng Feng; Jie Zhang 078; Yuxiao Dong; Yu Han 001; Huanbo Luan; Qian Xu 005; Qiang Yang 001; Jie Tang 001 (CoRR, 2020)

MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs. - Jifan Yu; Yuquan Wang; Qingyang Zhong; Gan Luo; Yiming Mao 005; Kai Sun; Wenzheng Feng; Wei Xu 017; Shulin Cao; Kaisheng Zeng; Zijun Yao 002; Lei Hou 001; et al. (CIKM, 2021)

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. - Tinglin Huang; Yuxiao Dong; Ming Ding 004; Zhen Yang 034; Wenzheng Feng; Xinyu Wang 001; Jie Tang 001 (KDD, 2021)

Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks. - Qingsong Lv; Ming Ding 004; Qiang Liu; Yuxiang Chen; Wenzheng Feng; Siming He; Chang Zhou; Jianguo Jiang; Yuxiao Dong; Jie Tang 001 (KDD, 2021)

XiaoMu: an AI-driven assistant for MOOCs. - Zhengyang Song; Jie Tang 001; Tracy Xiao Liu; Wenjiang Zheng; Lili Wu; Wenzheng Feng; Jing Zhang 001 (Sci. China Inf. Sci., 2021)

GRAND+: Scalable Graph Random Neural Networks. - Wenzheng Feng; Yuxiao Dong; Tinglin Huang; Ziqi Yin; Xu Cheng; Evgeny Kharlamov; Jie Tang 001 (WWW, 2022)

Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks. - Jibing Gong; Yao Wan 001; Ye Liu 006; Xuewen Li 005; Yi Zhao; Cheng Wang; Qing Li 026; Wenzheng Feng; Jie Tang 001 (CoRR, 2022)

WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window. - Yifan Zhu 001; Fangpeng Cong; Dan Zhang; Wenwen Gong; Qika Lin; Wenzheng Feng; Yuxiao Dong; Jie Tang 001 (KDD, 2023)

Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks. - Ming Zhou 004; Wenzheng Feng; Yifan Zhu 001; Dan Zhang; Yuxiao Dong; Jie Tang 001 (ECML/PKDD (6), 2023)

ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation. - Dan Zhang; Yifan Zhu 001; Yuxiao Dong; Yuandong Wang; Wenzheng Feng; Evgeny Kharlamov; Jie Tang 001 (WWW, 2023)

Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks. - Jibing Gong; Yao Wan 001; Ye Liu 006; Xuewen Li 005; Yi Zhao; Cheng Wang; Yuting Lin; Xiaohan Fang; Wenzheng Feng; Jingyi Zhang; Jie Tang 001 (ACM Trans. Web, 2023)

CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. - Tianyu Zhang; Yuxiang Ren; Wenzheng Feng; Weitao Du; Xuecang Zhang (DASFAA (6), 2024)

DropConn: Dropout Connection Based Random GNNs for Molecular Property Prediction. - Dan Zhang; Wenzheng Feng; Yuandong Wang; Zhongang Qi; Ying Shan; Jie Tang 001 (IEEE Trans. Knowl. Data Eng., 2024)

Learning Evolving Tools for Large Language Models. - Guoxin Chen; Zhong Zhang; Xin Cong; Fangda Guo; Yesai Wu; Yankai Lin; Wenzheng Feng; Yasheng Wang (ICLR, 2025)

Tencent Meeting forensics based on memory reverse analysis. - Shilong Yu; Binglong Li; Lin Zhu; Heyu Zhang; Sen Yang; Zhangxiao Li; Wenzheng Feng (PeerJ Comput. Sci., 2025)

LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges. - Xu Cheng; Liang Yao; Feng He; Yukuo Cen; Yufei He; Chenhui Zhang; Wenzheng Feng; Hongyun Cai 001; Jie Tang 001 (CoRR, 2025)