Publications    [Google Scholar]

2023

TOIS'23	Robust Collaborative Filtering to Popularity Distribution Shift An Zhang, Wenchang Ma, Jingnan Zheng, Xiang Wang, Tat-Seng Chua
EMNLP'23	ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction Yaorui Shi, An Zhang*, Enzhi Zhang, Zhiyuan Liu, Xiang Wang
NeurIPS'23	Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua
NeurIPS'23	Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He
NeurIPS'23	Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua
ACM MM'23	Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation Wei Ji, Xiangyan Liu, An Zhang*, Yinwei Wei, Yongxin Ni, Xiang Wang
ACM MM'23	Redundancy-aware Transformer for Video Question Answering Yicong Li, Xun Yang, An Zhang, Chun Feng, Xiang Wang, Tat-Seng Chua
KDD'23	Discovering Dynamic Causal Space for DAG Structure Learning Fangfu Liu, Wenchang Ma, An Zhang*, Xiang Wang, Yueqi Duan, Tat-Seng Chua
WWW'23	Invariant Collaborative Filtering to Popularity Distribution Shift An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan, Tat-Seng Chua
ICLR'23	Boosting Causal Discovery via Adaptive Sample Reweighting An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua
WSDM'23	Cooperative Explanations of Graph Neural Networks Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

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	CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. Yunshan Ma, Yingzhi He, An Zhang*, Xiang Wang, Tat-Seng Chua.

2021

NeurIPS'21

Towards Multi-Grained Explainability for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He, Tat-Seng Chua

2020

SIGIR'20

Disentangled Graph Collaborative Filtering Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua.