A Crop-Based Multi-Branch Network for Matching Cost Computation. - Yu Chen; Youshen Xia; Chenwang Wu (CISP-BMEI, 2018)

Random Directional Attack for Fooling Deep Neural Networks. - Wenjian Luo; Chenwang Wu; Nan Zhou; Li Ni (CoRR, 2019)

Enhancing the privacy of negative surveys using negative combined categories. - Hao Jiang 023; Wenjian Luo; Binyao Duan; Chenwang Wu (Appl. Soft Comput., 2020)

Genetic Algorithm with Multiple Fitness Functions for Generating Adversarial Examples. - Chenwang Wu; Wenjian Luo; Nan Zhou; Peilan Xu; Tao Zhu 001 (CEC, 2021)

Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems. - Chenwang Wu; Defu Lian; Yong Ge; Zhihao Zhu 002; Enhong Chen (KDD, 2021)

Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. - Moritz Neun; Christian Eichenberger; Henry Martin; Markus Spanring; Rahul Siripurapu; Daniel Springer; Leyan Deng; Chenwang Wu; Defu Lian; Min Zhou 006; Martin Lumiste; Andrei Ilie; et al. (NeurIPS (Competition and Demos), 2021)

Fight Fire with Fire: Towards Robust Recommender Systems via Adversarial Poisoning Training. - Chenwang Wu; Defu Lian; Yong Ge; Zhihao Zhu 002; Enhong Chen; Senchao Yuan (SIGIR, 2021)

Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy. - Leyan Deng; Defu Lian; Chenwang Wu; Enhong Chen (NeurIPS, 2022)

Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation. - Zhihao Zhu 002; Chenwang Wu; Min Zhou 006; Hao Liao; Defu Lian; Enhong Chen (ECML/PKDD (3), 2022)

Towards Robust Recommender Systems via Triple Cooperative Defense. - Qingyang Wang 003; Defu Lian; Chenwang Wu; Enhong Chen (WISE, 2022)

Detecting adversarial examples by positive and negative representations. - Wenjian Luo; Chenwang Wu; Li Ni; Nan Zhou; Zhenya Zhang (Appl. Soft Comput., 2022)

Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting. - Leyan Deng; Chenwang Wu; Defu Lian; Min Zhou 006 (CoRR, 2022)

GridFormer: Spatial-Temporal Transformer Network for Citywide Crowd Flow Prediction. - Chaoqun Su; Chenwang Wu; Defu Lian (ECAI, 2023)

A Causality Inspired Framework for Model Interpretation. - Chenwang Wu; Xiting Wang; Defu Lian; Xing Xie 001; Enhong Chen (KDD, 2023)

Membership Inference Attacks Against Sequential Recommender Systems. - Zhihao Zhu 002; Chenwang Wu; Rui Fan; Defu Lian; Enhong Chen (WWW, 2023)

When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities. - Jin Chen 008; Zheng Liu 011; Xu Huang 008; Chenwang Wu; Qi Liu 003; Gangwei Jiang; Yuanhao Pu; Yuxuan Lei; Xiaolong Chen; Xingmei Wang 001; Defu Lian; Enhong Chen (CoRR, 2023)

Toward Robust Recommendation via Real-time Vicinal Defense. - Yichang Xu; Chenwang Wu; Defu Lian (CoRR, 2023)

Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity. - Zhihao Zhu 002; Chenwang Wu; Rui Fan; Yi Yang 042; Defu Lian; Enhong Chen (CoRR, 2023)

Model Stealing Attack against Recommender System. - Zhihao Zhu 002; Rui Fan; Chenwang Wu; Yi Yang 042; Defu Lian; Enhong Chen (CoRR, 2023)

MAD-Net: Multi-attention dense network for functional bone marrow segmentation. - Chuanbo Qin; Bin Zheng; Wanying Li; Hongbo Chen; Junying Zeng; Chenwang Wu; Shufen Liang; Jun Luo; Shuquan Zhou; Lin Xiao (Comput. Biol. Medicine, 2023)

Influence-Driven Data Poisoning for Robust Recommender Systems. - Chenwang Wu; Defu Lian; Yong Ge; Zhihao Zhu 002; Enhong Chen (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Securing recommender system via cooperative training. - Qingyang Wang 003; Chenwang Wu; Defu Lian; Enhong Chen (World Wide Web (WWW), 2023)

Markov-Driven Graph Convolutional Networks for Social Spammer Detection. - Leyan Deng; Chenwang Wu; Defu Lian; Yongji Wu; Enhong Chen (IEEE Trans. Knowl. Data Eng., 2023)

Out-of-Distribution Generalization via Style and Spuriousness Eliminating. - Kaiyu Jin; Chenwang Wu; Defu Lian (ICME, 2024)

Learning from Highly Sparse Spatio-temporal Data. - Leyan Deng; Chenwang Wu; Defu Lian; Enhong Chen (NeurIPS, 2024)

Understanding Privacy Risks of Embeddings Induced by Large Language Models. - Zhihao Zhu 002; Ninglu Shao; Defu Lian; Chenwang Wu; Zheng Liu 011; Yi Yang 042; Enhong Chen (CoRR, 2024)

Boosting Factorization Machines via Saliency-Guided Mixup. - Chenwang Wu; Defu Lian; Yong Ge; Min Zhou 006; Enhong Chen; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

When large language models meet personalization: perspectives of challenges and opportunities. - Jin Chen 008; Zheng Liu 011; Xu Huang 008; Chenwang Wu; Qi Liu 003; Gangwei Jiang; Yuanhao Pu; Yuxuan Lei; Xiaolong Chen; Xingmei Wang 001; Kai Zheng 001; Defu Lian; et al. (World Wide Web (WWW), 2024)

Attacking Social Media via Behavior Poisoning. - Chenwang Wu; Defu Lian; Yong Ge; Min Zhou 006; Enhong Chen (ACM Trans. Knowl. Discov. Data, 2024)

Invariant representation learning via decoupling style and spurious features. - Ruimeng Li; Yuanhao Pu; Zhaoyi Li; Chenwang Wu; Hong Xie 004; Defu Lian (Mach. Learn., 2025)

Learning to Substitute Components for Compositional Generalization. - Zhaoyi Li; Gangwei Jiang; Chenwang Wu; Ying Wei 001; Defu Lian; Enhong Chen (CoRR, 2025)

Efficient Machine Unlearning via Influence Approximation. - Jiawei Liu; Chenwang Wu; Defu Lian; Enhong Chen (CoRR, 2025)