Publications (Google Scholar)

2023

WWW'23	Invariant Collaborative Filtering to Popularity Distribution Shift An Zhang, Jingnan Zheng, Xiang Wang*, Yancheng Yuan, Tat-Seng Chua
WWW'23	Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum Yuan Gao, Xiang Wang*, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
WWW'23	GIF: A General Graph Unlearning Strategy via Influence Function Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang*, Xiangnan He
ICLR'23	Boosting Causal Discovery via Adaptive Sample Reweighting An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang*, Tat-Seng Chua
ICSE'23	Learning Graph-based Code Representations for Source-level Functional Similarity Detection Jiahao Liu, Jun Zeng, Xiang Wang*, Zhenkai Liang
WSDM'23	Cooperative Explanations of Graph Neural Networks Junfeng Fang, Xiang Wang*, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua
WSDM'23	Alleviating Structural Distribution Shift in Graph Anomaly Detection Yuan Gao, Xiang Wang*, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

2022

NeurIPS'22	Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering. An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua
ICML'22	Let Invariant Rationale Discovery inspire Graph Contrastive Learning. Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua.
ICLR'22	Discovering invariant rationales for graph neural networks. YingXin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua.
TPAMI'22	Reinforced Causal Explainer for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua
KDD'22	Causal Attention for Interpretable and Generalizable Graph Classification. Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua.
KDD'22	CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. Yunshan Ma, Yingzhi He, An Zhang, Xiang Wang, Tat-Seng Chua.
CVPR'22	Invariant Grounding for Video Question Answering. Yicong Li, Xiang Wang, Junbin Xiao, Wei Ji, Tat-Seng Chua.
CVPR'22	Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose Estimation. Zhenguang Liu, Runyang Feng, Haoming Chen, Shuang Wu, Yixing Gao, Yunjun Gao, Xiang Wang.
IEEE S&P'22	Shadewatcher: Recommendation-guided Cyber Threat Analysis Using System Audit Records. Jun Zeng, Xiang Wang, Jiahao Liu, Yinfang Chen, Zhenkai Liang, Tat-Seng Chua, Zheng Leong Chua.
ISSTA'22	TELL: Log Level Suggestions via Modeling Multi-level Code Block Information. Jiahao Liu, Jun Zeng, Xiang Wang, Kaihang Ji, Zhenkai Liang.
TOIS'22	Time-aware Path Reasoning on Knowledge Graph for Recommendation. Yuyue Zhao, Xiang Wang, Jiawei Chen, Wei Tang, Yashen Wang, Xiangnan He, Haiyong Xie.
WWW'22	Cross Pairwise Ranking for Unbiased Item Recommendation. Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang.
TKDE'22	Causal Inference for Knowledge Graph based Recommendation. Yinwei Wei, Xiang Wang, Liqiang Nie, Shaoyu Li, Tat-Seng Chua.
TKDE'22	A survey on neural recommendation: From collaborative filtering to content and context enriched recommendation. Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang.
IJCAI'22	Copy Motion From One to Another: Fake Motion Video Generation. Zhenguang Liu, Sifan Wu, Chejian Xu, Xiang Wang, Lei Zhu, Shuang Wu, Fuli Feng.

2021

NeurIPS'21	Towards Multi-Grained Explainability for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He, Tat-Seng Chua
WWW'21	Learning Intents behind Interactions with Knowledge Graph for Recommendation Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua
SIGIR'21	Self-supervised graph learning for recommendation. Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie.
ACM MM'21	Contrastive learning for cold-start recommendation. Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan Li, Xuanping Li, Tat-Seng Chua.
TMM'21	Hierarchical user intent graph network for multimedia recommendation. Yinwei Wei, Xiang Wang, Xiangnan He, Liqiang Nie, Yong Rui, Tat-Seng Chua.

2020

WWW'20	Reinforced Negative Sampling over Knowledge Graph for Recommendation Xiang Wang, Yaokun Xu, Xiangnan He, Yinxin Cao, Meng Wang, Tat-Seng Chua.
SIGIR'20	Disentangled Graph Collaborative Filtering Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua.
SIGIR'20	LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang.
SIGIR'20	Hierarchical Fashion Graph Network for Personalised Outfit Recommendation. Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, Tat-Seng Chua.
ACM MM'20	Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback. Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Tat-Seng Chua.
ACM MM'20	How to Learn Item Representation for Cold-Start Multimedia Recommendation?. Xiaoyu Du, Xiang Wang, Xiangnan He, Zechao Li, Jinhui Tang, Tat-Seng Chua.
AAAI'20	Zero-Shot Ingredient Recognition by Multi-Relational Graph Convolutional Network. Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua.
IJCAI'20	Smart Contract Vulnerability Detection Using Graph Neural Networks. Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, Qinming He.
IJCAI'20	Bilinear Graph Neural Network with Neighbor Interactions. Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng, Yongdong Zhang.
KDD'20	Interactive Path Reasoning on Graph for Conversational Recommendation. Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua.
IPM'20	MGAT: Multimodal Graph Attention Network for Recommendation. Zhulin Tao, Yinwei Wei, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua.
IPM'20	HoAFM: A High-order Attentive Factorization Machine for CTR Prediction. Zhulin Tao, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua.

2019

KDD'19	KGAT: Knowledge Graph Attention Network for Recommendation Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua.
SIGIR'19	Neural Graph Collaborative Filtering Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua.
SIGIR'19	Interpretable Fashion Matching with Rich Attributes. Xun Yang, Xiangnan He, Xiang Wang, Yunshan Ma, Fuli Feng, Meng Wang, Tat-Seng Chua.
AAAI'19	Explainable Reasoning over Knowledge Graph Paths for Recommendation. Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua.
WWW'19	Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preference. Yixin Cao, Xiang Wang, Xiangnan He, Zikun Hu, Tat-Seng Chua.
TIP'19	Neural multimodal cooperative learning toward micro-video understanding. Yinwei Wei, Xiang Wang, Weili Guan, Liqiang Nie, Zhouchen Lin, Baoquan Chen.
ACM MM'19	MMGCN: Multi-modal graph convolution network for personalized recommendation of micro-video. Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong, Tat-Seng Chua.
TOIS'19	Temporal Relational Ranking for Stock Prediction. Fuli Feng, Xiangnan He, Xiang Wang, Cheng Luo, Yiqun Liu, Tat-Seng Chua.
TOIS'19	Deep Item-based Collaborative Filtering for Top-N Recommendation. Feng Xue, Xiangnan He, Xiang Wang, Jiandong Xu, Kai Liu, Richang Hong.

2018

WWW'18	TEM: Tree-enhanced Embedding Model for Explainable Recommendation. Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie, Tat-Seng Chua.
TIP'18	Online data organizer: micro-video categorization by structure-guided multimodal dictionary learning. Meng Liu, Liqiang Nie, Xiang Wang, Qi Tian, Baoquan Chen.
ACM MM'18	Crossmodal Moment Localization in Videos. Meng Liu, Xiang Wang, Liqiang Nie, Qi Tian, Baoquan Chen, Tat-Seng Chua.
SIGIR'18	Attentive Moment Retrieval in Videos. Meng Liu, Xiang Wang, Liqiang Nie, Xiangnan He, Baoquan Chen, Tat-Seng Chua.
SIGIR'18	A Personal Privacy Preserving Framework. Xuemeng Song, Xiang Wang, Liqiang Nie, Xiangnan He, Zhumin Chen, Wei Liu.
IJCAI'18	Outer Product-based Neural Collaborative Filtering. Xiangnan He, Xiaoyu Du, Xiang Wang, Feng Tian, Jinhui Tang, Tat-Seng Chua.

2017

SIGIR'17	Item Silk Road: Recommending Items from Information Domains to Social Users. Xiang Wang, Xiangnan He, Liqiang Nie, Tat-Seng Chua.
SIGIR'17	Computational Social Indicators: A Case Study of Chinese University Ranking. Fuli Feng, Liqiang Nie, Xiang Wang, Richang Hong, Tat-Seng Chua.
TOIS'17	Unifying Virtual and Physical Worlds: Learning towards Local and Global Consistency. Xiang Wang, Liqiang Nie, Xuemeng Song, Dongxiang Zhang, Tat-Seng Chua.
ACM MM'17	Enhancing Micro-video Understanding by Harnessing External Sounds. Liqiang Nie, Xiang Wang, Jianglong Zhang, Xiangnan He, Hanwang Zhang, Richang Hong, Qi Tian.
TKDE'17	Data-Driven Answer Selection in Community QA Systems. Liqiang Nie, Xiaochi Wei, Dongxiang Zhang, Xiang Wang, Zhipeng Gao, Yi Yang.

2016

ACM MM'16	Shorter-is-Better: Venue Category Estimation from Micro-Video. Jianglong Zhang, Liqiang Nie, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua.
ACM MM'16	Micro Tells Macro: Predicting the Popularity of Micro-Videos via a Transductive Model. Jingyuan Chen, Xuemeng Song, Liqiang Nie, Xiang Wang, Hanwang Zhang, Tat-Seng Chua.