Recording How-Provenance on Probabilistic Databases. - Ming Gao 001; Xiangnan He 001; Cheqing Jin; Xiaoling Wang 004; Aoying Zhou (APWeb, 2010)

Mining Scientific Terms and their Definitions: A Study of the ACL Anthology. - Yiping Jin; Min-Yen Kan; Jun-Ping Ng; Xiangnan He 001 (EMNLP, 2013)

Predicting the popularity of web 2.0 items based on user comments. - Xiangnan He 001; Ming Gao 001; Min-Yen Kan; Yiqun Liu 001; Kazunari Sugiyama (SIGIR, 2014)

Comment-based multi-view clustering of web 2.0 items. - Xiangnan He 001; Min-Yen Kan; Peichu Xie; Xiao Chen 004 (WWW, 2014)

VELDA: Relating an Image Tweet's Text and Images. - Tao Chen 008; Hany M. SalahEldeen; Xiangnan He 001; Min-Yen Kan; Dongyuan Lu (AAAI, 2015)

TriRank: Review-aware Explainable Recommendation by Modeling Aspects. - Xiangnan He 001; Tao Chen 008; Min-Yen Kan; Xiao Chen 004 (CIKM, 2015)

Differential spread strategy: An incentive for advertisement dissemination. - Xiao Chen 004; Min Liu 001; Yaqin Zhou; Zhongcheng Li; Shuang Chen; Xiangnan He 001 (ISCC, 2015)

Context-aware Image Tweet Modelling and Recommendation. - Tao Chen 008; Xiangnan He 001; Min-Yen Kan (ACM Multimedia, 2016)

Shorter-is-Better: Venue Category Estimation from Micro-Video. - Jianglong Zhang; Liqiang Nie; Xiang Wang 010; Xiangnan He 001; Xianglin Huang; Tat-Seng Chua (ACM Multimedia, 2016)

Fast Matrix Factorization for Online Recommendation with Implicit Feedback. - Xiangnan He 001; Hanwang Zhang; Min-Yen Kan; Tat-Seng Chua (SIGIR, 2016)

Discrete Collaborative Filtering. - Hanwang Zhang; Fumin Shen; Wei Liu 005; Xiangnan He 001; Huanbo Luan; Tat-Seng Chua (SIGIR, 2016)

SMASC 2017: First International Workshop on Social Media Analytics for Smart Cities. - Manjira Sinha; Xiangnan He 001; Alessandro Bozzon; Sandya Mannarswamy; Pradeep K. Murukannaiah; Tridib Mukherjee (CIKM, 2017)

SWIM: A Simple Word Interaction Model for Implicit Discourse Relation Recognition. - Wenqiang Lei; Xuancong Wang; Meichun Liu; Ilija Ilievski; Xiangnan He 001; Min-Yen Kan (IJCAI, 2017)

Representativeness-aware Aspect Analysis for Brand Monitoring in Social Media. - Lizi Liao; Xiangnan He 001; Zhaochun Ren; Liqiang Nie; Huan Xu; Tat-Seng Chua (IJCAI, 2017)

Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. - Jun Xiao 001; Hao Ye; Xiangnan He 001; Hanwang Zhang; Fei Wu 001; Tat-Seng Chua (IJCAI, 2017)

How Personality Affects our Likes: Towards a Better Understanding of Actionable Images. - Francesco Gelli; Xiangnan He 001; Tao Chen 008; Tat-Seng Chua (ACM Multimedia, 2017)

Multiview and Multimodal Pervasive Indoor Localization. - Zhenguang Liu; Li Cheng 001; Anan Liu; Luming Zhang; Xiangnan He 001; Roger Zimmermann (ACM Multimedia, 2017)

Enhancing Micro-video Understanding by Harnessing External Sounds. - Liqiang Nie; Xiang Wang 010; Jianglong Zhang; Xiangnan He 001; Hanwang Zhang; Richang Hong; Qi Tian 001 (ACM Multimedia, 2017)

Video Question Answering via Gradually Refined Attention over Appearance and Motion. - Dejing Xu; Zhou Zhao 001; Jun Xiao 001; Fei Wu 001; Hanwang Zhang; Xiangnan He 001; Yueting Zhuang (ACM Multimedia, 2017)

Neural Factorization Machines for Sparse Predictive Analytics. - Xiangnan He 001; Tat-Seng Chua (SIGIR, 2017)

Embedding Factorization Models for Jointly Recommending Items and User Generated Lists. - Da Cao; Liqiang Nie; Xiangnan He 001; Xiaochi Wei; Shunzhi Zhu; Tat-Seng Chua (SIGIR, 2017)

Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. - Jingyuan Chen; Hanwang Zhang; Xiangnan He 001; Liqiang Nie; Wei Liu 005; Tat-Seng Chua (SIGIR, 2017)

Item Silk Road: Recommending Items from Information Domains to Social Users. - Xiang Wang 010; Xiangnan He 001; Liqiang Nie; Tat-Seng Chua (SIGIR, 2017)

A Generic Coordinate Descent Framework for Learning from Implicit Feedback. - Immanuel Bayer; Xiangnan He 001; Bhargav Kanagal; Steffen Rendle (WWW, 2017)

Neural Collaborative Filtering. - Xiangnan He 001; Lizi Liao; Hanwang Zhang; Liqiang Nie; Xia Hu 001; Tat-Seng Chua (WWW, 2017)

Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search. - Lei Zhu 002; Zi Huang; Xiaobai Liu; Xiangnan He 001; Jingkuan Song; Xiaofang Zhou 001 (CoRR, 2017)

Version-sensitive mobile App recommendation. - Da Cao; Liqiang Nie; Xiangnan He 001; Xiaochi Wei; Jialie Shen 001; Shunxiang Wu; Tat-Seng Chua (Inf. Sci., 2017)

A Truthful Incentive Mechanism for Online Recruitment in Mobile Crowd Sensing System. - Xiao Chen 004; Min Liu 001; Yaqin Zhou; Zhongcheng Li; Shuang Chen; Xiangnan He 001 (Sensors, 2017)

BiRank: Towards Ranking on Bipartite Graphs. - Xiangnan He 001; Ming Gao 001; Min-Yen Kan; Dingxian Wang (IEEE Trans. Knowl. Data Eng., 2017)

Discrete Multimodal Hashing With Canonical Views for Robust Mobile Landmark Search. - Lei Zhu 002; Zi Huang; Xiaobai Liu; Xiangnan He 001; Jiande Sun 001; Xiaofang Zhou 001 (IEEE Trans. Multim., 2017)

Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts. - Da Cao; Xiangnan He 001; Liqiang Nie; Xiaochi Wei; Xia Hu 001; Shunxiang Wu; Tat-Seng Chua (ACM Trans. Inf. Syst., 2017)

Group-Pair Convolutional Neural Networks for Multi-View Based 3D Object Retrieval. - Zan Gao; Deyu Wang; Xiangnan He 001; Hua Zhang 003 (AAAI, 2018)

Batch IS NOT Heavy: Learning Word Representations From All Samples. - Xin Xin 003; Fajie Yuan; Xiangnan He 001; Joemon M. Jose (ACL (1), 2018)

Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures. - Wenqiang Lei; Xisen Jin; Min-Yen Kan; Zhaochun Ren; Xiangnan He 001; Dawei Yin (ACL (1), 2018)

A Graph-Theoretic Fusion Framework for Unsupervised Entity Resolution. - Dongxiang Zhang; Long Guo; Xiangnan He 001; Jie Shao 001; Sai Wu; Heng Tao Shen (ICDE, 2018)

Outer Product-based Neural Collaborative Filtering. - Xiangnan He 001; Xiaoyu Du 002; Xiang Wang 010; Feng Tian; Jinhui Tang 001; Tat-Seng Chua (IJCAI, 2018)

A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction. - Zhiyong Cheng 001; Ying Ding; Xiangnan He 001; Lei Zhu 002; Xuemeng Song; Mohan S. Kankanhalli (IJCAI, 2018)

Improving Implicit Recommender Systems with View Data. - Jingtao Ding; Guanghui Yu; Xiangnan He 001; Yuhan Quan; Yong Li 008; Tat-Seng Chua; Depeng Jin; Jiajie Yu (IJCAI, 2018)

Discrete Factorization Machines for Fast Feature-based Recommendation. - Han Liu; Xiangnan He 001; Fuli Feng; Liqiang Nie; Rui Liu 019; Hanwang Zhang (IJCAI, 2018)

Cross-Domain Depression Detection via Harvesting Social Media. - Tiancheng Shen; Jia Jia 001; Guangyao Shen; Fuli Feng; Xiangnan He 001; Huanbo Luan; Jie Tang 001; Thanassis Tiropanis; Tat-Seng Chua; Wendy Hall 001 (IJCAI, 2018)

Recommendation Technologies for Multimedia Content. - Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (ICMR, 2018)

Beyond the Product: Discovering Image Posts for Brands in Social Media. - Francesco Gelli; Tiberio Uricchio; Xiangnan He 001; Alberto Del Bimbo; Tat-Seng Chua (ACM Multimedia, 2018)

Interpretable Multimodal Retrieval for Fashion Products. - Lizi Liao; Xiangnan He 001; Bo Zhao; Chong-Wah Ngo; Tat-Seng Chua (ACM Multimedia, 2018)

Knowledge-aware Multimodal Dialogue Systems. - Lizi Liao; Yunshan Ma; Xiangnan He 001; Richang Hong; Tat-Seng Chua (ACM Multimedia, 2018)

Venue Prediction for Social Images by Exploiting Rich Temporal Patterns in LBSNs. - Jingyuan Chen; Xiangnan He 001; Xuemeng Song; Hanwang Zhang; Liqiang Nie; Tat-Seng Chua (MMM (2), 2018)

BiNE: Bipartite Network Embedding. - Ming Gao 001; Leihui Chen; Xiangnan He 001; Aoying Zhou (SIGIR, 2018)

Adversarial Personalized Ranking for Recommendation. - Xiangnan He 001; Zhankui He; Xiaoyu Du 002; Tat-Seng Chua (SIGIR, 2018)

Attentive Group Recommendation. - Da Cao; Xiangnan He 001; Lianhai Miao; Yahui An; Chao Yang 015; Richang Hong (SIGIR, 2018)

Attentive Moment Retrieval in Videos. - Meng Liu 006; Xiang Wang 010; Liqiang Nie; Xiangnan He 001; Baoquan Chen; Tat-Seng Chua (SIGIR, 2018)

Fast Scalable Supervised Hashing. - Xin Luo 006; Liqiang Nie; Xiangnan He 001; Ye Wu; Zhen-Duo Chen 001; Xin-Shun Xu (SIGIR, 2018)

Information Discovery in E-commerce: Half-day SIGIR 2018 Tutorial. - Zhaochun Ren; Xiangnan He 001; Dawei Yin; Maarten de Rijke (SIGIR, 2018)

A Personal Privacy Preserving Framework: I Let You Know Who Can See What. - Xuemeng Song; Xiang Wang 010; Liqiang Nie; Xiangnan He 001; Zhumin Chen; Wei Liu 005 (SIGIR, 2018)

fBGD: Learning Embeddings From Positive Unlabeled Data with BGD. - Fajie Yuan; Xin Xin 003; Xiangnan He 001; Guibing Guo; Weinan Zhang 001; Tat-Seng Chua; Joemon M. Jose (UAI, 2018)

An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data. - Jingtao Ding; Fuli Feng; Xiangnan He 001; Guanghui Yu; Yong Li 008; Depeng Jin (WWW (Companion Volume), 2018)

Learning on Partial-Order Hypergraphs. - Fuli Feng; Xiangnan He 001; Yiqun Liu 001; Liqiang Nie; Tat-Seng Chua (WWW, 2018)

TEM: Tree-enhanced Embedding Model for Explainable Recommendation. - Xiang Wang 010; Xiangnan He 001; Fuli Feng; Liqiang Nie; Tat-Seng Chua (WWW, 2018)

Aesthetic-based Clothing Recommendation. - Wenhui Yu; Huidi Zhang; Xiangnan He 001; Xu Chen 017; Li Xiong 001; Zheng Qin 003 (WWW, 2018)

A Simple but Hard-to-Beat Baseline for Session-based Recommendations. - Fajie Yuan; Alexandros Karatzoglou; Ioannis Arapakis; Joemon M. Jose; Xiangnan He 001 (CoRR, 2018)

Learning Recommender Systems from Multi-Behavior Data. - Chen Gao 001; Xiangnan He 001; Dahua Gan; Xiangning Chen; Fuli Feng; Yong Li 008; Tat-Seng Chua; Depeng Jin (CoRR, 2018)

Sampler Design for Bayesian Personalized Ranking by Leveraging View Data. - Jingtao Ding; Guanghui Yu; Xiangnan He 001; Yong Li 008; Depeng Jin (CoRR, 2018)

Visually-aware Collaborative Food Recommendation. - Xiaoyan Gao; Fuli Feng; Xiangnan He 001; Heyan Huang; Xinyu Guan; Chong Feng 001; Zhaoyan Ming; Tat-Seng Chua (CoRR, 2018)

Improving Stock Movement Prediction with Adversarial Training. - Fuli Feng; Huimin Chen; Xiangnan He 001; Ji Ding 005; Maosong Sun 001; Tat-Seng Chua (CoRR, 2018)

Fast Matrix Factorization with Non-Uniform Weights on Missing Data. - Xiangnan He 001; Jinhui Tang 001; Xiaoyu Du 002; Richang Hong; Tongwei Ren; Tat-Seng Chua (CoRR, 2018)

Scene Dynamics: Counterfactual Critic Multi-Agent Training for Scene Graph Generation. - Long Chen 016; Hanwang Zhang; Jun Xiao 001; Xiangnan He 001; Shiliang Pu; Shih-Fu Chang (CoRR, 2018)

NAIS: Neural Attentive Item Similarity Model for Recommendation. - Xiangnan He 001; Zhankui He; Jingkuan Song; Zhenguang Liu; Yu-Gang Jiang 001; Tat-Seng Chua (IEEE Trans. Knowl. Data Eng., 2018)

Attributed Social Network Embedding. - Lizi Liao; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (IEEE Trans. Knowl. Data Eng., 2018)

Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering. - Xiangpeng Li; Jingkuan Song; Lianli Gao; Xianglong Liu 001; Wenbing Huang 001; Xiangnan He 001; Chuang Gan 001 (AAAI, 2019)

Explainable Reasoning over Knowledge Graphs for Recommendation. - Xiang Wang 010; Dingxian Wang; Canran Xu; Xiangnan He 001; Yixin Cao 002; Tat-Seng Chua (AAAI, 2019)

Learning and Reasoning on Graph for Recommendation. - Xiang Wang 010; Xiangnan He 001; Tat-Seng Chua (CIKM, 2019)

Counterfactual Critic Multi-Agent Training for Scene Graph Generation. - Long Chen 016; Hanwang Zhang; Jun Xiao 001; Xiangnan He 001; Shiliang Pu; Shih-Fu Chang (ICCV, 2019)

Neural Multi-task Recommendation from Multi-behavior Data. - Chen Gao 001; Xiangnan He 001; Dahua Gan; Xiangning Chen; Fuli Feng; Yong Li 008; Tat-Seng Chua; Depeng Jin (ICDE, 2019)

Semi-supervised User Profiling with Heterogeneous Graph Attention Networks. - Weijian Chen 001; Yulong Gu; Zhaochun Ren; Xiangnan He 001; Hongtao Xie; Tong Guo; Dawei Yin; Yongdong Zhang 001 (IJCAI, 2019)

Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network. - Liang Chen 001; Yang Liu 245; Xiangnan He 001; Lianli Gao; Zibin Zheng (IJCAI, 2019)

Reinforced Negative Sampling for Recommendation with Exposure Data. - Jingtao Ding; Yuhan Quan; Xiangnan He 001; Yong Li 008; Depeng Jin (IJCAI, 2019)

Enhancing Stock Movement Prediction with Adversarial Training. - Fuli Feng; Huimin Chen; Xiangnan He 001; Ji Ding 005; Maosong Sun 001; Tat-Seng Chua (IJCAI, 2019)

CFM: Convolutional Factorization Machines for Context-Aware Recommendation. - Xin Xin 003; Bo Chen 023; Xiangnan He 001; Dong Wang 024; Yue Ding 001; Joemon M. Jose (IJCAI, 2019)

λOpt: Learn to Regularize Recommender Models in Finer Levels. - Yihong Chen; Bei Chen; Xiangnan He 001; Chen Gao 001; Yong Li 008; Jian-Guang Lou; Yue Wang 007 (KDD, 2019)

Modeling Extreme Events in Time Series Prediction. - Daizong Ding; Mi Zhang 001; Xudong Pan; Min Yang 002; Xiangnan He 001 (KDD, 2019)

Sets2Sets: Learning from Sequential Sets with Neural Networks. - Haoji Hu; Xiangnan He 001 (KDD, 2019)

KGAT: Knowledge Graph Attention Network for Recommendation. - Xiang Wang 010; Xiangnan He 001; Yixin Cao 002; Meng Liu 006; Tat-Seng Chua (KDD, 2019)

Mixed-dish Recognition with Contextual Relation Networks. - Lixi Deng; Jingjing Chen 001; Qianru Sun; Xiangnan He 001; Sheng Tang; Zhaoyan Ming; Yongdong Zhang 001; Tat-Seng Chua (ACM Multimedia, 2019)

Learning Subjective Attributes of Images from Auxiliary Sources. - Francesco Gelli; Tiberio Uricchio; Xiangnan He 001; Alberto Del Bimbo; Tat-Seng Chua (ACM Multimedia, 2019)

MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video. - Yinwei Wei; Xiang Wang 010; Liqiang Nie; Xiangnan He 001; Richang Hong; Tat-Seng Chua (ACM Multimedia, 2019)

Neural Graph Collaborative Filtering. - Xiang Wang 010; Xiangnan He 001; Meng Wang 001; Fuli Feng; Tat-Seng Chua (SIGIR, 2019)

Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. - Xin Xin 003; Xiangnan He 001; Yongfeng Zhang; Yongdong Zhang 001; Joemon M. Jose (SIGIR, 2019)

Interpretable Fashion Matching with Rich Attributes. - Xun Yang 001; Xiangnan He 001; Xiang Wang 010; Yunshan Ma; Fuli Feng; Meng Wang 001; Tat-Seng Chua (SIGIR, 2019)

A Simple Convolutional Generative Network for Next Item Recommendation. - Fajie Yuan; Alexandros Karatzoglou; Ioannis Arapakis; Joemon M. Jose; Xiangnan He 001 (WSDM, 2019)

Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences. - Yixin Cao 002; Xiang Wang 010; Xiangnan He 001; Zikun Hu; Tat-Seng Chua (WWW, 2019)

Cross-domain Recommendation Without Sharing User-relevant Data. - Chen Gao 001; Xiangning Chen; Fuli Feng; Kai Zhao; Xiangnan He 001; Yong Li 008; Depeng Jin (WWW, 2019)

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels. - Yihong Chen; Bei Chen; Xiangnan He 001; Chen Gao 001; Yong Li 008; Jian-Guang Lou; Yue Wang 007 (CoRR, 2019)

Modeling the Past and Future Contexts for Session-based Recommendation. - Fajie Yuan; Xiangnan He 001; Guibing Guo; Zhezhao Xu; Jian Xiong; Xiuqiang He 001 (CoRR, 2019)

Special issue on multimedia recommendation and multi-modal data analysis. - Xiangnan He 001; Zhenguang Liu; Hanwang Zhang; Chong-Wah Ngo; Svebor Karaman; Yongfeng Zhang (Multim. Syst., 2019)

Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering. - Xiaoyu Du 002; Xiangnan He 001; Fajie Yuan; Jinhui Tang 001; Zhiguang Qin; Tat-Seng Chua (ACM Trans. Inf. Syst., 2019)

Temporal Relational Ranking for Stock Prediction. - Fuli Feng; Xiangnan He 001; Xiang Wang 010; Cheng Luo 001; Yiqun Liu 001; Tat-Seng Chua (ACM Trans. Inf. Syst., 2019)

Attentive Aspect Modeling for Review-Aware Recommendation. - Xinyu Guan; Zhiyong Cheng 001; Xiangnan He 001; Yongfeng Zhang; Zhibo Zhu; Qinke Peng; Tat-Seng Chua (ACM Trans. Inf. Syst., 2019)

Deep Item-based Collaborative Filtering for Top-N Recommendation. - Feng Xue 002; Xiangnan He 001; Xiang Wang 010; Jiandong Xu; Kai Liu; Richang Hong (ACM Trans. Inf. Syst., 2019)

Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning. - Daizong Ding; Mi Zhang 001; Xudong Pan; Min Yang 002; Xiangnan He 001 (AAAI, 2020)

Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction. - Haozhe Wu; Zhiyuan Hu; Jia Jia 001; Yaohua Bu; Xiangnan He 001; Tat-Seng Chua (AAAI, 2020)

Syndrome-aware Herb Recommendation with Multi-Graph Convolution Network. - Yuanyuan Jin; Wei Zhang 056; Xiangnan He 001; Xinyu Wang 017; Xiaoling Wang 004 (ICDE, 2020)

Improving Neural Relation Extraction with Implicit Mutual Relations. - Jun Kuang; Yixin Cao 002; Jianbing Zheng 001; Xiangnan He 001; Ming Gao 001; Aoying Zhou (ICDE, 2020)

Price-aware Recommendation with Graph Convolutional Networks. - Yu Zheng 010; Chen Gao 001; Xiangnan He 001; Yong Li 008; Depeng Jin (ICDE, 2020)

Modeling Personalized Out-of-Town Distances in Location Recommendation. - Daizong Ding; Mi Zhang 001; Xudong Pan; Min Yang 002; Xiangnan He 001 (ICDM, 2020)

Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning. - Tianxin Wei; Ziwei Wu; Ruirui Li 002; Ziniu Hu; Fuli Feng; Xiangnan He 001; Yizhou Sun; Wei Wang 010 (ICDM, 2020)

Bilinear Graph Neural Network with Neighbor Interactions. - Hongmin Zhu; Fuli Feng; Xiangnan He 001; Xiang Wang 010; Yan Li 068; Kai Zheng 001; Yongdong Zhang 001 (IJCAI, 2020)

Enterprise Cooperation and Competition Analysis with a Sign-Oriented Preference Network. - Le Dai; Yu Yin 002; Chuan Qin 002; Tong Xu 001; Xiangnan He 001; Enhong Chen; Hui Xiong 001 (KDD, 2020)

Interactive Path Reasoning on Graph for Conversational Recommendation. - Wenqiang Lei; Gangyi Zhang; Xiangnan He 001; Yisong Miao; Xiang Wang 010; Liang Chen 001; Tat-Seng Chua (KDD, 2020)

STRONG: Spatio-Temporal Reinforcement Learning for Cross-Modal Video Moment Localization. - Da Cao; Yawen Zeng; Meng Liu 006; Xiangnan He 001; Meng Wang 001; Zheng Qin 001 (ACM Multimedia, 2020)

How to Learn Item Representation for Cold-Start Multimedia Recommendation? - Xiaoyu Du 002; Xiang Wang 010; Xiangnan He 001; Zechao Li; Jinhui Tang 001; Tat-Seng Chua (ACM Multimedia, 2020)

Heterogeneous Fusion of Semantic and Collaborative Information for Visually-Aware Food Recommendation. - Lei Meng 001; Fuli Feng; Xiangnan He 001; Xiaoyan Gao; Tat-Seng Chua (ACM Multimedia, 2020)

Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback. - Yinwei Wei; Xiang Wang 010; Liqiang Nie; Xiangnan He 001; Tat-Seng Chua (ACM Multimedia, 2020)

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. - Xiangnan He 001; Kuan Deng; Xiang Wang 010; Yan Li 068; Yong-Dong Zhang 001; Meng Wang 001 (SIGIR, 2020)

Bundle Recommendation with Graph Convolutional Networks. - Jianxin Chang; Chen Gao 001; Xiangnan He 001; Depeng Jin; Yong Li 008 (SIGIR, 2020)

FinIR 2020: The First Workshop on Information Retrieval in Finance. - Fuli Feng; Cheng Luo 001; Xiangnan He 001; Yiqun Liu 001; Tat-Seng Chua (SIGIR, 2020)

Modeling Personalized Item Frequency Information for Next-basket Recommendation. - Haoji Hu; Xiangnan He 001; Jinyang Gao; Zhi-Li Zhang (SIGIR, 2020)

Multi-behavior Recommendation with Graph Convolutional Networks. - Bowen Jin; Chen Gao 001; Xiangnan He 001; Depeng Jin; Yong Li 008 (SIGIR, 2020)

Conversational Recommendation: Formulation, Methods, and Evaluation. - Wenqiang Lei; Xiangnan He 001; Maarten de Rijke; Tat-Seng Chua (SIGIR, 2020)

Hierarchical Fashion Graph Network for Personalized Outfit Recommendation. - Xingchen Li; Xiang Wang 010; Xiangnan He 001; Long Chen 016; Jun Xiao 001; Tat-Seng Chua (SIGIR, 2020)

Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines. - Yang Liu 245; Xianzhuo Xia; Liang Chen 001; Xiangnan He 001; Carl Yang 001; Zibin Zheng (SIGIR, 2020)

Disentangled Graph Collaborative Filtering. - Xiang Wang 010; Hongye Jin; An Zhang 003; Xiangnan He 001; Tong Xu 001; Tat-Seng Chua (SIGIR, 2020)

Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation. - Fajie Yuan; Xiangnan He 001; Alexandros Karatzoglou; Liguang Zhang (SIGIR, 2020)

How to Retrain Recommender System?: A Sequential Meta-Learning Method. - Yang Zhang 072; Fuli Feng; Chenxu Wang; Xiangnan He 001; Meng Wang 001; Yan Li 068; Yongdong Zhang 001 (SIGIR, 2020)

Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems. - Wenqiang Lei; Xiangnan He 001; Yisong Miao; Qingyun Wu; Richang Hong; Min-Yen Kan; Tat-Seng Chua (WSDM, 2020)

NLP4REC: The WSDM 2020 Workshop on Natural Language Processing for Recommendations. - Pengjie Ren; Zhaochun Ren; Fei Sun 001; Xiangnan He 001; Dawei Yin; Maarten de Rijke (WSDM, 2020)

Reinforced Negative Sampling over Knowledge Graph for Recommendation. - Xiang Wang 010; Yaokun Xu; Xiangnan He 001; Yixin Cao 002; Meng Wang 001; Tat-Seng Chua (WWW, 2020)

Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation. - Fajie Yuan; Xiangnan He 001; Haochuan Jiang; Guibing Guo; Jian Xiong; Zhezhao Xu; Yilin Xiong (WWW, 2020)

Parameter-Efficient Transfer from Sequential Behaviors for User Profiling and Recommendation. - Fajie Yuan; Xiangnan He 001; Alexandros Karatzoglou; Liguang Zhang (CoRR, 2020)

Graph Convolution Machine for Context-aware Recommender System. - Jiancan Wu; Xiangnan He 001; Xiang Wang 010; Qifan Wang 001; Weijian Chen 001; Jianxun Lian; Xing Xie 001; Yongdong Zhang 001 (CoRR, 2020)

Bilinear Graph Neural Network with Node Interactions. - Hongmin Zhu; Fuli Feng; Xiangnan He 001; Xiang Wang 010; Yan Li 068; Kai Zheng 001; Yongdong Zhang 001 (CoRR, 2020)

Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions. - Fuli Feng; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (CoRR, 2020)

A Survey of Adversarial Learning on Graphs. - Liang Chen 001; Jintang Li; Jiaying Peng; Tao Xie; Zengxu Cao; Kun Xu; Xiangnan He 001; Zibin Zheng (CoRR, 2020)

Graph Learning Approaches to Recommender Systems: A Review. - Shoujin Wang; Liang Hu 004; Yan Wang 002; Xiangnan He 001; Quan Z. Sheng; Mehmet A. Orgun; Longbing Cao; Nan Wang 009; Francesco Ricci 001; Philip S. Yu (CoRR, 2020)

Disentangling User Interest and Popularity Bias for Recommendation with Causal Embedding. - Yu Zheng 010; Chen Gao 001; Xiang Li 067; Xiangnan He 001; Yong Li 008; Depeng Jin (CoRR, 2020)

Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning. - Hande Dong; Zhaolin Ding; Xiangnan He 001; Fuli Feng; Shuxian Bi (CoRR, 2020)

"Click" Is Not Equal to "Like": Counterfactual Recommendation for Mitigating Clickbait Issue. - Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (CoRR, 2020)

Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. - Fuli Feng; Weiran Huang 002; Xin Xin 003; Xiangnan He 001; Tat-Seng Chua (CoRR, 2020)

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. - Tianxin Wei; Fuli Feng; Jiawei Chen 007; Chufeng Shi; Ziwei Wu; Jinfeng Yi; Xiangnan He 001 (CoRR, 2020)

Deep Learning for Matching in Search and Recommendation. - Jun Xu 001; Xiangnan He 001; Hang Li 001 (Found. Trends Inf. Retr., 2020)

HoAFM: A High-order Attentive Factorization Machine for CTR Prediction. - Zhulin Tao; Xiang Wang 010; Xiangnan He 001; Xianglin Huang; Tat-Seng Chua (Inf. Process. Manag., 2020)

MGAT: Multimodal Graph Attention Network for Recommendation. - Zhulin Tao; Yinwei Wei; Xiang Wang 010; Xiangnan He 001; Xianglin Huang; Tat-Seng Chua (Inf. Process. Manag., 2020)

Video-based recipe retrieval. - Da Cao; Ning Han; Hao Chen 051; Xiaochi Wei; Xiangnan He 001 (Inf. Sci., 2020)

Report on the international workshop on natural language processing for recommendations (NLP4REC 2020) workshop held at WSDM 2020. - Xiao Huang 001; Pengjie Ren; Zhaochun Ren; Fei Sun 001; Xiangnan He 001; Dawei Yin; Maarten de Rijke (SIGIR Forum, 2020)

ATM: An Attentive Translation Model for Next-Item Recommendation. - Bin Wu 019; Xiangnan He 001; Zhongchuan Sun; Liang Chen 001; Yangdong Ye (IEEE Trans. Ind. Informatics, 2020)

Generative Adversarial Active Learning for Unsupervised Outlier Detection. - Ye-Zheng Liu 001; Zhe Li; Chong Zhou; Yuanchun Jiang; Jianshan Sun; Meng Wang 001; Xiangnan He 001 (IEEE Trans. Knowl. Data Eng., 2020)

Adversarial Training Towards Robust Multimedia Recommender System. - Jinhui Tang 001; Xiaoyu Du 002; Xiangnan He 001; Fajie Yuan; Qi Tian 001; Tat-Seng Chua (IEEE Trans. Knowl. Data Eng., 2020)

Hierarchical Attention Network for Visually-Aware Food Recommendation. - Xiaoyan Gao; Fuli Feng; Xiangnan He 001; Heyan Huang; Xinyu Guan; Chong Feng 001; Zhaoyan Ming; Tat-Seng Chua (IEEE Trans. Multim., 2020)

Knowledge-Based Topic Model for Multi-Modal Social Event Analysis. - Feng Xue 002; Richang Hong; Xiangnan He 001; Jianwei Wang; Shengsheng Qian; Changsheng Xu (IEEE Trans. Multim., 2020)

Fast Matrix Factorization With Nonuniform Weights on Missing Data. - Xiangnan He 001; Jinhui Tang 001; Xiaoyu Du 002; Richang Hong; Tongwei Ren; Tat-Seng Chua (IEEE Trans. Neural Networks Learn. Syst., 2020)

Improving Implicit Recommender Systems with Auxiliary Data. - Jingtao Ding; Guanghui Yu; Yong Li 008; Xiangnan He 001; Depeng Jin (ACM Trans. Inf. Syst., 2020)

Learning Visual Elements of Images for Discovery of Brand Posts. - Francesco Gelli; Tiberio Uricchio; Xiangnan He 001; Alberto Del Bimbo; Tat-Seng Chua (ACM Trans. Multim. Comput. Commun. Appl., 2020)

Empowering Language Understanding with Counterfactual Reasoning. - Fuli Feng; Jizhi Zhang; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (ACL/IJCNLP (Findings), 2021)

A Deep Learning Framework for Self-evolving Hierarchical Community Detection. - Daizong Ding; Mi Zhang 001; Hanrui Wang 002; Xudong Pan; Min Yang 002; Xiangnan He 001 (CIKM, 2021)

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network. - Junkang Wu; Wentao Shi 002; Xuezhi Cao; Jiawei Chen 007; Wenqiang Lei; Fuzheng Zhang; Wei Wu 014; Xiangnan He 001 (CIKM, 2021)

Time horizon-aware modeling of financial texts for stock price prediction. - Fuli Feng; Xiang Wang 010; Xiangnan He 001; Ritchie Ng; Tat-Seng Chua (ICAIF, 2021)

On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner. - Na Li; Renyu Zhu; Xiaoxu Zhou; Xiangnan He 001; Wenyuan Cai; Ming Gao 001; Aoying Zhou (ICDE, 2021)

Graph Learning based Recommender Systems: A Review. - Shoujin Wang; Liang Hu 004; Yan Wang 002; Xiangnan He 001; Quan Z. Sheng; Mehmet A. Orgun; Longbing Cao; Francesco Ricci 001; Philip S. Yu (IJCAI, 2021)

Deconfounded Recommendation for Alleviating Bias Amplification. - Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Xiang Wang 010; Tat-Seng Chua (KDD, 2021)

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. - Tianxin Wei; Fuli Feng; Jiawei Chen 007; Ziwei Wu; Jinfeng Yi; Xiangnan He 001 (KDD, 2021)

Selective Dependency Aggregation for Action Classification. - Yi Tan 001; Yanbin Hao; Xiangnan He 001; Yinwei Wei; Xun Yang 001 (ACM Multimedia, 2021)

Towards Multi-Grained Explainability for Graph Neural Networks. - Xiang Wang 010; Ying-Xin Wu 002; An Zhang 003; Xiangnan He 001; Tat-Seng Chua (NeurIPS, 2021)

Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021. - Jiawei Chen 007; Xiang Wang 010; Fuli Feng; Xiangnan He 001 (RecSys, 2021)

AutoDebias: Learning to Debias for Recommendation. - Jiawei Chen 007; Hande Dong; Yang Qiu; Xiangnan He 001; Xin Xin 003; Liang Chen 001; Guli Lin; Keping Yang (SIGIR, 2021)

Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. - Fuli Feng; Weiran Huang 002; Xiangnan He 001; Xin Xin 003; Qifan Wang 001; Tat-Seng Chua (SIGIR, 2021)

Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue. - Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (SIGIR, 2021)

Self-supervised Graph Learning for Recommendation. - Jiancan Wu; Xiang Wang 010; Fuli Feng; Xiangnan He 001; Liang Chen 001; Jianxun Lian; Xing Xie 001 (SIGIR, 2021)

Causal Intervention for Leveraging Popularity Bias in Recommendation. - Yang Zhang 072; Fuli Feng; Xiangnan He 001; Tianxin Wei; Chonggang Song; Guohui Ling; Yongdong Zhang 001 (SIGIR, 2021)

Denoising Implicit Feedback for Recommendation. - Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Liqiang Nie; Tat-Seng Chua (WSDM, 2021)

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation. - Hande Dong; Jiawei Chen 007; Fuli Feng; Xiangnan He 001; Shuxian Bi; Zhaolin Ding; Peng Cui 001 (WWW, 2021)

Learning Intents behind Interactions with Knowledge Graph for Recommendation. - Xiang Wang 010; Tinglin Huang; Dingxian Wang; Yancheng Yuan; Zhenguang Liu; Xiangnan He 001; Tat-Seng Chua (WWW, 2021)

Disentangling User Interest and Conformity for Recommendation with Causal Embedding. - Yu Zheng 010; Chen Gao 001; Xiang Li 067; Xiangnan He 001; Yong Li 008; Depeng Jin (WWW, 2021)

Advances and challenges in conversational recommender systems: A survey. - Chongming Gao; Wenqiang Lei; Xiangnan He 001; Maarten de Rijke; Tat-Seng Chua (AI Open, 2021)

Structure-enhanced meta-learning for few-shot graph classification. - Shunyu Jiang; Fuli Feng; Weijian Chen 001; Xiang Li 067; Xiangnan He 001 (AI Open, 2021)

A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation. - Le Wu; Xiangnan He 001; Xiang Wang 010; Kun Zhang 015; Meng Wang 001 (CoRR, 2021)

Probabilistic and Variational Recommendation Denoising. - Yu Wang; Xin Xin 003; Zaiqiao Meng; Xiangnan He 001; Joemon M. Jose; Fuli Feng (CoRR, 2021)

Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. - Chen Gao 001; Yu Zheng 010; Nian Li; Yinfeng Li; Yingrong Qin; Jinghua Piao; Yuhan Quan; Jianxin Chang; Depeng Jin; Xiangnan He 001; Yong Li 008 (CoRR, 2021)

Hierarchical User Intent Graph Network forMultimedia Recommendation. - Yinwei Wei; Xiang Wang 010; Xiangnan He 001; Liqiang Nie; Yong Rui; Tat-Seng Chua (CoRR, 2021)

GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback. - Yinwei Wei; Xiang Wang 010; Liqiang Nie; Xiangnan He 001; Tat-Seng Chua (CoRR, 2021)

Learning Robust Recommender from Noisy Implicit Feedback. - Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Liqiang Nie; Tat-Seng Chua (CoRR, 2021)

Deconfounded Training for Graph Neural Networks. - Yongduo Sui; Xiang Wang 010; Jiancan Wu; Xiangnan He 001; Tat-Seng Chua (CoRR, 2021)

M-BPR: A novel approach to improving BPR for recommendation with multi-type pair-wise preferences. - Yeon-Chang Lee; Taeho Kim 003; Jaeho Choi; Xiangnan He 001; Sang-Wook Kim (Inf. Sci., 2021)

Social-Enhanced Attentive Group Recommendation. - Da Cao; Xiangnan He 001; Lianhai Miao; Guangyi Xiao; Hao Chen 051; Jia Xu 005 (IEEE Trans. Knowl. Data Eng., 2021)

Sampler Design for Bayesian Personalized Ranking by Leveraging View Data. - Jingtao Ding; Guanghui Yu; Xiangnan He 001; Fuli Feng; Yong Li 008; Depeng Jin (IEEE Trans. Knowl. Data Eng., 2021)

Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. - Fuli Feng; Xiangnan He 001; Jie Tang 001; Tat-Seng Chua (IEEE Trans. Knowl. Data Eng., 2021)

Learning to Recommend With Multiple Cascading Behaviors. - Chen Gao 001; Xiangnan He 001; Dahua Gan; Xiangning Chen; Fuli Feng; Yong Li 008; Tat-Seng Chua; Lina Yao 001; Yang Song 001; Depeng Jin (IEEE Trans. Knowl. Data Eng., 2021)

Generating Face Images With Attributes for Free. - Yaoyao Liu 001; Qianru Sun; Xiangnan He 001; An-An Liu; Yuting Su 001; Tat-Seng Chua (IEEE Trans. Neural Networks Learn. Syst., 2021)

CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation. - Jiawei Chen 007; Chengquan Jiang; Can Wang 001; Sheng Zhou 004; Yan Feng; Chun Chen 001; Martin Ester; Xiangnan He 001 (ACM Trans. Inf. Syst., 2021)

Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-start Users. - Shijun Li 002; Wenqiang Lei; Qingyun Wu; Xiangnan He 001; Peng Jiang 002; Tat-Seng Chua (ACM Trans. Inf. Syst., 2021)

Socializing the Videos: A Multimodal Approach for Social Relation Recognition. - Tong Xu 001; Peilun Zhou; Linkang Hu; Xiangnan He 001; Yao Hu 002; Enhong Chen (ACM Trans. Multim. Comput. Commun. Appl., 2021)

Visually aware recommendation with aesthetic features. - Wenhui Yu; Xiangnan He 001; Jian Pei 001; Xu Chen 017; Li Xiong 001; Jinfei Liu; Zheng Qin 003 (VLDB J., 2021)

Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning. - Moxin Li; Fuli Feng; Hanwang Zhang; Xiangnan He 001; Fengbin Zhu; Tat-Seng Chua (ACL (1), 2022)

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems. - Chongming Gao; Shijun Li 002; Wenqiang Lei; Jiawei Chen 007; Biao Li; Peng Jiang 002; Xiangnan He 001; Jiaxin Mao; Tat-Seng Chua (CIKM, 2022)

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos. - Chongming Gao; Shijun Li 002; Yuan Zhang 024; Jiawei Chen 007; Biao Li; Wenqiang Lei; Peng Jiang 002; Xiangnan He 001 (CIKM, 2022)

Self-Supervised Learning for Recommendation. - Chao Huang 001; Lianghao Xia; Xiang Wang 010; Xiangnan He 001; Dawei Yin (CIKM, 2022)

Group Contextualization for Video Recognition. - Yanbin Hao; Hao Zhang 047; Chong-Wah Ngo; Xiangnan He 001 (CVPR, 2022)

DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning. - Chuhan Wu; Fangzhao Wu; Xiangnan He 001; Yongfeng Huang 001 (EMNLP (Findings), 2022)

Discovering Invariant Rationales for Graph Neural Networks. - Yingxin Wu 002; Xiang Wang 010; An Zhang 003; Xiangnan He 001; Tat-Seng Chua (ICLR, 2022)

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. - Sihang Li 002; Xiang Wang 010; An Zhang 003; Yingxin Wu 002; Xiangnan He 001; Tat-Seng Chua (ICML, 2022)

Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. - Sihao Ding 003; Peng Wu 012; Fuli Feng; Yitong Wang; Xiangnan He 001; Yong Liao; Yongdong Zhang 001 (KDD, 2022)

Causal Attention for Interpretable and Generalizable Graph Classification. - Yongduo Sui; Xiang Wang 010; Jiancan Wu; Min Lin; Xiangnan He 001; Tat-Seng Chua (KDD, 2022)

Multi-directional Knowledge Transfer for Few-Shot Learning. - Shuo Wang 008; Xinyu Zhang 022; Yanbin Hao; Chengbing Wang; Xiangnan He 001 (ACM Multimedia, 2022)

Invariant Representation Learning for Multimedia Recommendation. - Xiaoyu Du 002; Zike Wu; Fuli Feng; Xiangnan He 001; Jinhui Tang 001 (ACM Multimedia, 2022)

Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation. - Yanbin Hao; Jingru Duan; Hao Zhang 047; Bin Zhu 006; Pengyuan Zhou; Xiangnan He 001 (ACM Multimedia, 2022)

Hierarchical Hourglass Convolutional Network for Efficient Video Classification. - Yi Tan 001; Yanbin Hao; Hao Zhang 047; Shuo Wang 008; Xiangnan He 001 (ACM Multimedia, 2022)

Parameterization of Cross-token Relations with Relative Positional Encoding for Vision MLP. - Zhicai Wang; Yanbin Hao; Xingyu Gao 001; Hao Zhang 047; Shuo Wang 008; Tingting Mu; Xiangnan He 001 (ACM Multimedia, 2022)

Interpolative Distillation for Unifying Biased and Debiased Recommendation. - Sihao Ding 003; Fuli Feng; Xiangnan He 001; Jinqiu Jin; Wenjie Wang 007; Yong Liao; Yongdong Zhang 001 (SIGIR, 2022)

Self-Supervised Learning for Recommender System. - Chao Huang 001; Xiang Wang 010; Xiangnan He 001; Dawei Yin (SIGIR, 2022)

Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task. - Keqin Bao; Yu Wan 004; Dayiheng Liu; Baosong Yang; Wenqiang Lei; Xiangnan He 001; Derek F. Wong; Jun Xie (WMT, 2022)

Graph Neural Networks for Recommender System. - Chen Gao 001; Xiang Wang 010; Xiangnan He 001; Yong Li 008 (WSDM, 2022)

Accepted Tutorials at The Web Conference 2022. - Riccardo Tommasini 001; Senjuti Basu Roy; Xuan Wang 008; Hongwei Wang; Heng Ji 001; Jiawei Han 001; Preslav Nakov; Giovanni Da San Martino; Firoj Alam; Markus Schedl; Elisabeth Lex; Akash Bharadwaj; et al. (WWW (Companion Volume), 2022)

IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search. - Dian Cheng; Jiawei Chen 007; Wenjun Peng; Wenqin Ye; Fuyu Lv; Tao Zhuang; Xiaoyi Zeng; Xiangnan He 001 (WWW, 2022)

Cross Pairwise Ranking for Unbiased Item Recommendation. - Qi Wan; Xiangnan He 001; Xiang Wang 010; Jiancan Wu; Wei Guo 006; Ruiming Tang (WWW, 2022)

Causal Representation Learning for Out-of-Distribution Recommendation. - Wenjie Wang 007; Xinyu Lin 001; Fuli Feng; Xiangnan He 001; Min Lin; Tat-Seng Chua (WWW, 2022)

Learning Robust Recommenders through Cross-Model Agreement. - Yu Wang; Xin Xin 003; Zaiqiao Meng; Joemon M. Jose; Fuli Feng; Xiangnan He 001 (WWW, 2022)

On the Effectiveness of Sampled Softmax Loss for Item Recommendation. - Jiancan Wu; Xiang Wang 010; Xingyu Gao 001; Jiawei Chen 007; Hongcheng Fu; Tianyu Qiu; Xiangnan He 001 (CoRR, 2022)

Deconfounding to Explanation Evaluation in Graph Neural Networks. - Ying-Xin Wu 002; Xiang Wang 010; An Zhang 003; Xia Hu 001; Fuli Feng; Xiangnan He 001; Tat-Seng Chua (CoRR, 2022)

KuaiRec: A Fully-observed Dataset for Recommender Systems. - Chongming Gao; Shijun Li 002; Wenqiang Lei; Biao Li; Peng Jiang 002; Jiawei Chen 007; Xiangnan He 001; Jiaxin Mao; Tat-Seng Chua (CoRR, 2022)

Rumor Detection with Self-supervised Learning on Texts and Social Graph. - Yuan Gao 015; Xiang Wang 010; Xiangnan He 001; Huamin Feng; Yongdong Zhang 001 (CoRR, 2022)

Differentiable Invariant Causal Discovery. - Yu Wang; An Zhang 003; Xiang Wang 010; Xiangnan He 001; Tat-Seng Chua (CoRR, 2022)

Explainable Sparse Knowledge Graph Completion via High-order Graph Reasoning Network. - Weijian Chen 001; Yixin Cao 002; Fuli Feng; Xiangnan He 001; Yongdong Zhang 001 (CoRR, 2022)

Adversarial Causal Augmentation for Graph Covariate Shift. - Yongduo Sui; Xiang Wang 010; Jiancan Wu; An Zhang 003; Xiangnan He 001 (CoRR, 2022)

Graph convolution machine for context-aware recommender system. - Jiancan Wu; Xiangnan He 001; Xiang Wang 010; Qifan Wang 001; Weijian Chen 001; Jianxun Lian; Xing Xie 001 (Frontiers Comput. Sci., 2022)

Exploring lottery ticket hypothesis in media recommender systems. - Yanfang Wang; Yongduo Sui; Xiang Wang 010; Zhenguang Liu; Xiangnan He 001 (Int. J. Intell. Syst., 2022)

Learning to Compose and Reason with Language Tree Structures for Visual Grounding. - Richang Hong; Daqing Liu; Xiaoyu Mo; Xiangnan He 001; Hanwang Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A KG-Enhanced Multi-Graph Neural Network for Attentive Herb Recommendation. - Yuanyuan Jin; Wendi Ji; Wei Zhang 056; Xiangnan He 001; Xinyu Wang 017; Xiaoling Wang 004 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Attention in Attention: Modeling Context Correlation for Efficient Video Classification. - Yanbin Hao; Shuo Wang 008; Pei Cao; Xinjian Gao; Tong Xu 001; Jinmeng Wu; Xiangnan He 001 (IEEE Trans. Circuits Syst. Video Technol., 2022)

Spatio-Temporal Collaborative Module for Efficient Action Recognition. - Yanbin Hao; Shuo Wang 008; Yi Tan 001; Xiangnan He 001; Zhenguang Liu; Meng Wang 001 (IEEE Trans. Image Process., 2022)

Cross-domain Recommendation with Bridge-Item Embeddings. - Chen Gao 001; Yong Li 008; Fuli Feng; Xiangning Chen; Kai Zhao; Xiangnan He 001; Depeng Jin (ACM Trans. Knowl. Discov. Data, 2022)

Learning Vertex Representations for Bipartite Networks. - Ming Gao 001; Xiangnan He 001; Leihui Chen; Tingting Liu; Jinglin Zhang; Aoying Zhou (IEEE Trans. Knowl. Data Eng., 2022)

Modelling High-Order Social Relations for Item Recommendation. - Yang Liu 245; Liang Chen 001; Xiangnan He 001; Jiaying Peng; Zibin Zheng; Jie Tang 001 (IEEE Trans. Knowl. Data Eng., 2022)

A Survey on Large-Scale Machine Learning. - Meng Wang 001; Weijie Fu; Xiangnan He 001; Shijie Hao; Xindong Wu 001 (IEEE Trans. Knowl. Data Eng., 2022)

Modeling Product's Visual and Functional Characteristics for Recommender Systems. - Bin Wu 019; Xiangnan He 001; Yun Chen; Liqiang Nie; Kai Zheng 001; Yangdong Ye (IEEE Trans. Knowl. Data Eng., 2022)

Hierarchical User Intent Graph Network for Multimedia Recommendation. - Yinwei Wei; Xiang Wang 010; Xiangnan He 001; Liqiang Nie; Yong Rui; Tat-Seng Chua (IEEE Trans. Multim., 2022)

Graph Technologies for User Modeling and Recommendation: Introduction to the Special Issue - Part 1. - Xiangnan He 001; Zhaochun Ren; Emine Yilmaz; Marc Najork; Tat-Seng Chua (ACM Trans. Inf. Syst., 2022)

Introduction to the Special Section on Graph Technologies for User Modeling and Recommendation, Part 2. - Xiangnan He 001; Zhaochun Ren; Emine Yilmaz; Marc Najork; Tat-Seng Chua (ACM Trans. Inf. Syst., 2022)

Multimedia Recommender Systems: Algorithms and Challenges. - Yashar Deldjoo; Markus Schedl; Balázs Hidasi; Yinwei Wei; Xiangnan He 001 (Recommender Systems Handbook, 2022)

Knowledge Graph Embedding by Normalizing Flows. - Changyi Xiao; Xiangnan He 001; Yixin Cao 002 (AAAI, 2023)

Counterfactual Active Learning for Out-of-Distribution Generalization. - Xun Deng; Wenjie Wang 007; Fuli Feng; Hanwang Zhang; Xiangnan He 001; Yong Liao (ACL (1), 2023)

How Can Contrastive Pre-training Benefit Audio-Visual Segmentation? A Study from Supervised and Zero-shot Perspectives. - Jiarui Yu; Haoran Li; Yanbin Hao; Jinmeng Wu; Tong Xu 001; Shuo Wang 008; Xiangnan He 001 (BMVC, 2023)

The 1st Workshop on Recommendation with Generative Models. - Wenjie Wang 007; Yong Liu 020; Yang Zhang 072; Weiwen Liu; Fuli Feng; Xiangnan He 001; Aixin Sun (CIKM, 2023)

Bi-Directional Distribution Alignment for Transductive Zero-Shot Learning. - Zhicai Wang; Yanbin Hao; Tingting Mu; Ouxiang Li; Shuo Wang 008; Xiangnan He 001 (CVPR, 2023)

Attack Prompt Generation for Red Teaming and Defending Large Language Models. - Boyi Deng; Wenjie Wang 007; Fuli Feng; Yang Deng 002; Qifan Wang 001; Xiangnan He 001 (EMNLP (Findings), 2023)

Modelling High-Order Social Relations for Item Recommendation (Extended Abstract). - Yang Liu 245; Liang Chen 001; Xiangnan He 001; Jiaying Peng; Zibin Zheng; Jie Tang 001 (ICDE, 2023)

LightMIRM: Light Meta-learned Invariant Risk Minimization for Trustworthy Loan Default Prediction. - Meng Jiang; Yang Zhang 072; Yuan Gao 020; Yansong Wang; Fuli Feng; Xiangnan He 001 (ICDE, 2023)

Modeling Product's Visual and Functional Characteristics for Recommender Systems (Extended Abstract). - Bin Wu 019; Xiangnan He 001; Yu Chen 022; Liqiang Nie; Kai Zheng 001; Yangdong Ye (ICDE, 2023)

Discriminative-Invariant Representation Learning for Unbiased Recommendation. - Hang Pan 006; Jiawei Chen 007; Fuli Feng; Wentao Shi 002; Junkang Wu; Xiangnan He 001 (IJCAI, 2023)

Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning. - Jinda Lu; Shuo Wang 008; Xinyu Zhang 022; Yanbin Hao; Xiangnan He 001 (ACM Multimedia, 2023)

CgT-GAN: CLIP-guided Text GAN for Image Captioning. - Jiarui Yu; Haoran Li; Yanbin Hao; Bin Zhu 006; Tong Xu 001; Xiangnan He 001 (ACM Multimedia, 2023)

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis. - Junfeng Fang; Wei Liu 005; Yuan Gao 020; Zemin Liu; An Zhang 003; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2023)

Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. - Jinqiu Jin; Haoxuan Li 001; Fuli Feng; Sihao Ding 003; Peng Wu 012; Xiangnan He 001 (NeurIPS, 2023)

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. - Haoxuan Li 001; Kunhan Wu; Chunyuan Zheng 001; Yanghao Xiao; Hao Wang 049; Zhi Geng; Fuli Feng; Xiangnan He 001; Peng Wu 012 (NeurIPS, 2023)

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. - Yongduo Sui; Qitian Wu; Jiancan Wu; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2023)

Understanding Contrastive Learning via Distributionally Robust Optimization. - Junkang Wu; Jiawei Chen 007; Jiancan Wu; Wentao Shi 002; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2023)

Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. - Zhengyi Yang 007; Jiancan Wu; Zhicai Wang; Xiang Wang 010; Yancheng Yuan; Xiangnan He 001 (NeurIPS, 2023)

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. - Keqin Bao; Jizhi Zhang; Yang Zhang 072; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (RecSys, 2023)

ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. - Haoxuan Li 001; Taojun Hu; Zetong Xiong; Chunyuan Zheng 001; Fuli Feng; Xiangnan He 001; Xiao-Hua Zhou (RecSys, 2023)

RecAD: Towards A Unified Library for Recommender Attack and Defense. - Changsheng Wang; Jianbai Ye; Wenjie Wang 007; Chongming Gao; Fuli Feng; Xiangnan He 001 (RecSys, 2023)

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. - Jizhi Zhang; Keqin Bao; Yang Zhang 072; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (RecSys, 2023)

Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation. - Chongming Gao; Kexin Huang; Jiawei Chen 007; Yuan Zhang 024; Biao Li; Peng Jiang 002; Shiqi Wang 018; Zhong Zhang 004; Xiangnan He 001 (SIGIR, 2023)

Diffusion Recommender Model. - Wenjie Wang 007; Yiyan Xu; Fuli Feng; Xinyu Lin 001; Xiangnan He 001; Tat-Seng Chua (SIGIR, 2023)

Causal Recommendation: Progresses and Future Directions. - Wenjie Wang 007; Yang Zhang 072; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (SIGIR, 2023)

A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. - Zhengyi Yang 007; Xiangnan He 001; Jizhi Zhang; Jiancan Wu; Xin Xin 003; Jiawei Chen 007; Xiang Wang 010 (SIGIR, 2023)

Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation. - Yang Zhang 072; Tianhao Shi; Fuli Feng; Wenjie Wang 007; Dingxian Wang; Xiangnan He 001; Yongdong Zhang 001 (SIGIR, 2023)

Unbiased Knowledge Distillation for Recommendation. - Gang Chen; Jiawei Chen 007; Fuli Feng; Sheng Zhou 004; Xiangnan He 001 (WSDM, 2023)

Cooperative Explanations of Graph Neural Networks. - Junfeng Fang; Xiang Wang 010; An Zhang 003; Zemin Liu; Xiangnan He 001; Tat-Seng Chua (WSDM, 2023)

Alleviating Structural Distribution Shift in Graph Anomaly Detection. - Yuan Gao 020; Xiang Wang 010; Xiangnan He 001; Zhenguang Liu; Huamin Feng; Yongdong Zhang 001 (WSDM, 2023)

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. - Jiawei Chen 007; Junkang Wu; Jiancan Wu; Xuezhi Cao; Sheng Zhou 004; Xiangnan He 001 (WWW, 2023)

Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum. - Yuan Gao 020; Xiang Wang 010; Xiangnan He 001; Zhenguang Liu; Huamin Feng; Yongdong Zhang 001 (WWW, 2023)

On the Theories Behind Hard Negative Sampling for Recommendation. - Wentao Shi 002; Jiawei Chen 007; Fuli Feng; Jizhi Zhang; Junkang Wu; Chongming Gao; Xiangnan He 001 (WWW, 2023)

GIF: A General Graph Unlearning Strategy via Influence Function. - Jiancan Wu; Yi Yang 061; Yuchun Qian; Yongduo Sui; Xiang Wang 010; Xiangnan He 001 (WWW, 2023)

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion. - Wentao Shi 002; Junkang Wu; Xuezhi Cao; Jiawei Chen 007; Wenqiang Lei; Wei Wu 014; Xiangnan He 001 (CoRR, 2023)

Weakly Supervised Anomaly Detection: A Survey. - Minqi Jiang; Chaochuan Hou; Ao Zheng; Xiyang Hu; Songqiao Han; Hailiang Huang; Xiangnan He 001; Philip S. Yu; Yue Zhao 016 (CoRR, 2023)

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation. - Jiawei Chen 007; Junkang Wu; Jiancan Wu; Sheng Zhou 004; Xuezhi Cao; Xiangnan He 001 (CoRR, 2023)

Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors. - Keqin Bao; Yu Wan 004; Dayiheng Liu; Baosong Yang; Wenqiang Lei; Xiangnan He 001; Derek F. Wong; Jun Xie (CoRR, 2023)

Generative Recommendation: Towards Next-generation Recommender Paradigm. - Wenjie Wang 007; Xinyu Lin 001; Fuli Feng; Xiangnan He 001; Tat-Seng Chua (CoRR, 2023)

Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation. - Gangyi Zhang; Chongming Gao; Wenqiang Lei; Xiaojie Guo 002; Shijun Li 002; Lingfei Wu 001; Hongshen Chen; Zhuozhi Ding; Sulong Xu; Xiangnan He 001 (CoRR, 2023)

Recommendation Unlearning via Influence Function. - Yang Zhang 072; Zhiyu Hu; Yimeng Bai; Fuli Feng; Jiancan Wu; Qifan Wang 001; Xiangnan He 001 (CoRR, 2023)

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems. - Keqin Bao; Jizhi Zhang; Wenjie Wang 007; Yang Zhang 072; Zhengyi Yang 007; Yancheng Luo; Fuli Feng; Xiangnan He 001; Qi Tian 001 (CoRR, 2023)

Label Denoising through Cross-Model Agreement. - Yu Wang; Xin Xin 003; Zaiqiao Meng; Xiangnan He 001; Joemon M. Jose; Fuli Feng (CoRR, 2023)

Selective Volume Mixup for Video Action Recognition. - Yi Tan 001; Zhaofan Qiu; Yanbin Hao; Ting Yao; Xiangnan He 001; Tao Mei 001 (CoRR, 2023)

A Content-Driven Micro-Video Recommendation Dataset at Scale. - Yongxin Ni; Yu Cheng 011; Xiangyan Liu; Junchen Fu; Youhua Li; Xiangnan He 001; Yongfeng Zhang; Fajie Yuan (CoRR, 2023)

Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation. - Chengpeng Li 001; Zhengyi Yang 007; Jizhi Zhang; Jiancan Wu; Dingxian Wang; Xiangnan He 001; Xiang Wang 010 (CoRR, 2023)

Large Language Model Can Interpret Latent Space of Sequential Recommender. - Zhengyi Yang 007; Jiancan Wu; Yanchen Luo; Jizhi Zhang; Yancheng Yuan; An Zhang 003; Xiang Wang 010; Xiangnan He 001 (CoRR, 2023)

CAR: Consolidation, Augmentation and Regulation for Recipe Retrieval. - Fangzhou Song; Bin Zhu 006; Yanbin Hao; Shuo Wang 008; Xiangnan He 001 (CoRR, 2023)

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems. - Tianhao Shi; Yang Zhang 072; Zhijian Xu; Chong Chen 002; Fuli Feng; Xiangnan He 001; Qi Tian 001 (CoRR, 2023)

Reinforced Causal Explainer for Graph Neural Networks. - Xiang Wang 010; Yingxin Wu 002; An Zhang 003; Fuli Feng; Xiangnan He 001; Tat-Seng Chua (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions. - Fuli Feng; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (IEEE Trans. Knowl. Data Eng., 2023)

Adversarial Attack on Large Scale Graph. - Jintang Li; Tao Xie; Liang Chen 001; Fenfang Xie; Xiangnan He 001; Zibin Zheng (IEEE Trans. Knowl. Data Eng., 2023)

Incorporating Price into Recommendation With Graph Convolutional Networks. - Yu Zheng 010; Chen Gao 001; Xiangnan He 001; Depeng Jin; Yong Li 008 (IEEE Trans. Knowl. Data Eng., 2023)

Addressing Confounding Feature Issue for Causal Recommendation. - Xiangnan He 001; Yang Zhang 072; Fuli Feng; Chonggang Song; Lingling Yi; Guohui Ling; Yongdong Zhang 001 (ACM Trans. Inf. Syst., 2023)

Bias and Debias in Recommender System: A Survey and Future Directions. - Jiawei Chen 007; Hande Dong; Xiang Wang 010; Fuli Feng; Meng Wang 001; Xiangnan He 001 (ACM Trans. Inf. Syst., 2023)

Information Retrieval meets Large Language Models: A strategic report from Chinese IR community. - Qingyao Ai; Ting Bai; Zhao Cao; Yi Chang 001; Jiawei Chen 007; Zhumin Chen; Zhiyong Cheng 001; Shoubin Dong; Zhicheng Dou; Fuli Feng; Shen Gao; Jiafeng Guo; et al. (AI Open, 2023)

Interactive active learning for fairness with partial group label. - Zeyu Yang; Jizhi Zhang; Fuli Feng; Chongming Gao; Qifan Wang 001; Xiangnan He 001 (AI Open, 2023)

Boosting Hyperspectral Image Classification with Dual Hierarchical Learning. - Shuo Wang 008; Huixia Ben; Yanbin Hao; Xiangnan He 001; Meng Wang 001 (ACM Trans. Multim. Comput. Commun. Appl., 2023)

Joint Multi-Grained Popularity-Aware Graph Convolution Collaborative Filtering for Recommendation. - Kang Liu; Feng Xue 002; Xiangnan He 001; Dan Guo 001; Richang Hong (IEEE Trans. Comput. Soc. Syst., 2023)

Bundle Recommendation and Generation With Graph Neural Networks. - Jianxin Chang; Chen Gao 001; Xiangnan He 001; Depeng Jin; Yong Li 008 (IEEE Trans. Knowl. Data Eng., 2023)

User-Specific Adaptive Fine-Tuning for Cross-Domain Recommendations. - Lei Chen 072; Fajie Yuan; Jiaxi Yang; Xiangnan He 001; Chengming Li; Min Yang 007 (IEEE Trans. Knowl. Data Eng., 2023)

A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. - Chen Gao 001; Yu Zheng 010; Nian Li; Yinfeng Li; Yingrong Qin; Jinghua Piao; Yuhan Quan; Jianxin Chang; Depeng Jin; Xiangnan He 001; Yong Li 008 (Trans. Recomm. Syst., 2023)

CatGCN: Graph Convolutional Networks With Categorical Node Features. - Weijian Chen 001; Fuli Feng; Qifan Wang 001; Xiangnan He 001; Chonggang Song; Guohui Ling; Yongdong Zhang 001 (IEEE Trans. Knowl. Data Eng., 2023)

Time-aware Path Reasoning on Knowledge Graph for Recommendation. - Yuyue Zhao; Xiang Wang 010; Jiawei Chen 007; Yashen Wang; Wei Tang 015; Xiangnan He 001; Haiyong Xie 001 (ACM Trans. Inf. Syst., 2023)

GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. - Jiajia Chen; Xin Xin 003; Xianfeng Liang; Xiangnan He 001; Jun Liu 004 (IEEE Trans. Knowl. Data Eng., 2023)

A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation. - Le Wu; Xiangnan He 001; Xiang Wang 010; Kun Zhang 015; Meng Wang 001 (IEEE Trans. Knowl. Data Eng., 2023)

Graph-Augmented Co-Attention Model for Socio-Sequential Recommendation. - Bin Wu 019; Xiangnan He 001; Le Wu; Xue Zhang; Yangdong Ye (IEEE Trans. Syst. Man Cybern. Syst., 2023)

Rumor detection with self-supervised learning on texts and social graph. - Yuan Gao 020; Xiang Wang 010; Xiangnan He 001; Huamin Feng; Yong-Dong Zhang 001 (Frontiers Comput. Sci., 2023)

Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation. - Zihao Zhao 004; Jiawei Chen 007; Sheng Zhou 004; Xiangnan He 001; Xuezhi Cao; Fuzheng Zhang; Wei Wu 014 (IEEE Trans. Knowl. Data Eng., 2023)

LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization. - Honglei Zhang; Fangyuan Luo; Jun Wu 007; Xiangnan He 001; Yidong Li (ACM Trans. Inf. Syst., 2023)

Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation. - Chenxu Wang; Fuli Feng; Yang Zhang 072; Qifan Wang 001; Xunhan Hu; Xiangnan He 001 (IEEE Trans. Big Data, 2023)

GCRec: Graph-Augmented Capsule Network for Next-Item Recommendation. - Bin Wu 019; Xiangnan He 001; Qi Zhang 071; Meng Wang 001; Yangdong Ye (IEEE Trans. Neural Networks Learn. Syst., 2023)

Text-to-Image Generation for Abstract Concepts. - Jiayi Liao; Xu Chen 022; Qiang Fu 015; Lun Du; Xiangnan He 001; Xiang Wang 010; Shi Han; Dongmei Zhang 001 (AAAI, 2024)

Boosting Few-Shot Learning via Attentive Feature Regularization. - Xingyu Zhu; Shuo Wang 008; Jinda Lu; Yanbin Hao; Haifeng Liu; Xiangnan He 001 (AAAI, 2024)

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation. - Yang Zhang 072; Keqin Bao; Ming Yan; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (ACL (1), 2024)

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems. - Tianhao Shi; Yang Zhang 072; Zhijian Xu; Chong Chen 001; Fuli Feng; Xiangnan He 001; Qi Tian 001 (CIKM, 2024)

Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model. - Zhicai Wang; Longhui Wei; Tan Wang; Heyu Chen; Yanbin Hao; Xiang Wang 010; Xiangnan He 001; Qi Tian 001 (CVPR, 2024)

Towards 3D Molecule-Text Interpretation in Language Models. - Sihang Li 002; Zhiyuan Liu 001; Yanchen Luo; Xiang Wang 010; Xiangnan He 001; Kenji Kawaguchi; Tat-Seng Chua; Qi Tian 001 (ICLR, 2024)

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. - Haoxuan Li 001; Chunyuan Zheng 001; Sihao Ding 003; Peng Wu 012; Zhi Geng; Fuli Feng; Xiangnan He 001 (ICLR, 2024)

A3S: A General Active Clustering Method with Pairwise Constraints. - Xun Deng; Junlong Liu; Han Zhong; Fuli Feng; Chen Shen 003; Xiangnan He 001; Jieping Ye; Zheng Wang 027 (ICML, 2024)

Customizing Language Models with Instance-wise LoRA for Sequential Recommendation. - Xiaoyu Kong; Jiancan Wu; An Zhang 003; Leheng Sheng; Hui Lin; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2024)

β-DPO: Direct Preference Optimization with Dynamic β. - Junkang Wu; Yuexiang Xie; Zhengyi Yang 007; Jiancan Wu; Jinyang Gao; Bolin Ding; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2024)

LLaRA: Large Language-Recommendation Assistant. - Jiayi Liao; Sihang Li 002; Zhengyi Yang 007; Jiancan Wu; Yancheng Yuan; Xiang Wang 010; Xiangnan He 001 (SIGIR, 2024)

Large Language Models are Learnable Planners for Long-Term Recommendation. - Wentao Shi 002; Xiangnan He 001; Yang Zhang 072; Chongming Gao; Xinyue Li; Jizhi Zhang; Qifan Wang 001; Fuli Feng (SIGIR, 2024)

Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. - Tianhao Shi; Yang Zhang 072; Jizhi Zhang; Fuli Feng; Xiangnan He 001 (SIGIR, 2024)

Diffusion Models for Generative Outfit Recommendation. - Yiyan Xu; Wenjie Wang 007; Fuli Feng; Yunshan Ma; Jizhi Zhang; Xiangnan He 001 (SIGIR, 2024)

Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. - Zihao Zhao 004; Yi Jing; Fuli Feng; Jiancan Wu; Chongming Gao; Xiangnan He 001 (SIGIR, 2024)

Proactive Recommendation with Iterative Preference Guidance. - Shuxian Bi; Wenjie Wang 007; Hang Pan 006; Fuli Feng; Xiangnan He 001 (WWW (Companion Volume), 2024)

EXGC: Bridging Efficiency and Explainability in Graph Condensation. - Junfeng Fang; Xinglin Li; Yongduo Sui; Yuan Gao 020; Guibin Zhang; Kun Wang 056; Xiang Wang 010; Xiangnan He 001 (WWW, 2024)

Simulating Human Society with Large Language Model Agents: City, Social Media, and Economic System. - Chen Gao 001; Fengli Xu; Xu Chen 017; Xiang Wang 010; Xiangnan He 001; Yong Li 008 (WWW (Companion Volume), 2024)

Item-side Fairness of Large Language Model-based Recommendation System. - Meng Jiang; Keqin Bao; Jizhi Zhang; Wenjie Wang 007; Zhengyi Yang 007; Fuli Feng; Xiangnan He 001 (WWW, 2024)

Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. - Wentao Shi 002; Chenxu Wang; Fuli Feng; Yang Zhang 072; Wenjie Wang 007; Junkang Wu; Xiangnan He 001 (WWW, 2024)

The 2nd Workshop on Recommendation with Generative Models. - Wenjie Wang 007; Yang Zhang 072; Xinyu Lin 001; Fuli Feng; Weiwen Liu; Yong Liu 020; Xiangyu Zhao 001; Wayne Xin Zhao; Yang Song 008; Xiangnan He 001 (WWW (Companion Volume), 2024)

Large Language Models for Recommendation: Progresses and Future Directions. - Jizhi Zhang; Keqin Bao; Yang Zhang 072; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (WWW (Companion Volume), 2024)

Alleviating Structural Distribution Shift in Graph Anomaly Detection. - Yuan Gao 015; Xiang Wang 010; Xiangnan He 001; Zhenguang Liu; Huamin Feng; Yongdong Zhang 001 (CoRR, 2024)

EXGC: Bridging Efficiency and Explainability in Graph Condensation. - Junfeng Fang; Xinglin Li; Yongduo Sui; Yuan Gao 015; Guibin Zhang; Kun Wang 056; Xiang Wang 010; Xiangnan He 001 (CoRR, 2024)

DiFashion: Towards Personalized Outfit Generation and Recommendation. - Yiyan Xu; Wenjie Wang 007; Fuli Feng; Yunshan Ma; Jizhi Zhang; Xiangnan He 001 (CoRR, 2024)

Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning. - Wentao Shi 002; Xiangnan He 001; Yang Zhang 072; Chongming Gao; Xinyue Li; Jizhi Zhang; Qifan Wang 001; Fuli Feng (CoRR, 2024)

Exact and Efficient Unlearning for Large Language Model-based Recommendation. - Zhiyu Hu; Yang Zhang 072; Minghao Xiao; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

A Survey of Generative Search and Recommendation in the Era of Large Language Models. - Yongqi Li 001; Xinyu Lin 001; Wenjie Wang 007; Fuli Feng; Liang Pang; Wenjie Li 002; Liqiang Nie; Xiangnan He 001; Tat-Seng Chua (CoRR, 2024)

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation. - Yang Zhang 072; Keqin Bao; Ming Yang 001; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. - Hang Pan 006; Shuxian Bi; Wenjie Wang 007; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models. - Junfeng Fang; Houcheng Jiang; Kun Wang 042; Yunshan Ma; Xiang Wang 010; Xiangnan He 001; Tat-Seng Chua (CoRR, 2024)

α-DPO: Adaptive Reward Margin is What Direct Preference Optimization Needs. - Junkang Wu; Xue Wang 010; Zhengyi Yang 007; Jiancan Wu; Jinyang Gao; Bolin Ding; Xiang Wang 010; Xiangnan He 001 (CoRR, 2024)

RosePO: Aligning LLM-based Recommenders with Human Values. - Jiayi Liao; Xiangnan He 001; Ruobing Xie; Jiancan Wu; Yancheng Yuan; Xingwu Sun; Zhanhui Kang; Xiang Wang 010 (CoRR, 2024)

Personalized Image Generation with Large Multimodal Models. - Yiyan Xu; Wenjie Wang 007; Yang Zhang 072; Tang Biao; Peng Yan; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning. - Keqin Bao; Ming Yang 001; Yang Zhang 072; Jizhi Zhang; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

SPRec: Leveraging Self-Play to Debias Preference Alignment for Large Language Model-based Recommendations. - Chongming Gao; Ruijun Chen; Shuai Yuan 018; Kexin Huang; Yuanqing Yu; Xiangnan He 001 (CoRR, 2024)

Information Discovery in E-commerce. - Zhaochun Ren; Xiangnan He 001; Dawei Yin; Maarten de Rijke (Found. Trends Inf. Retr., 2024)

Feature Mixture on Pre-Trained Model for Few-Shot Learning. - Shuo Wang 008; Jinda Lu; Haiyang Xu 002; Yanbin Hao; Xiangnan He 001 (IEEE Trans. Image Process., 2024)

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System. - Chongming Gao; Shiqi Wang 018; Shijun Li 002; Jiawei Chen 007; Xiangnan He 001; Wenqiang Lei; Biao Li; Yuan Zhang 024; Peng Jiang 002 (ACM Trans. Inf. Syst., 2024)

Learning to Double-Check Model Prediction From a Causal Perspective. - Xun Deng; Fuli Feng; Xiang Wang 010; Xiangnan He 001; Hanwang Zhang; Tat-Seng Chua (IEEE Trans. Neural Networks Learn. Syst., 2024)

Causal Incremental Graph Convolution for Recommender System Retraining. - Sihao Ding 003; Fuli Feng; Xiangnan He 001; Yong Liao; Jun Shi; Yongdong Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning. - Yongduo Sui; Wenyu Mao; Shuyao Wang; Xiang Wang 010; Jiancan Wu; Xiangnan He 001; Tat-Seng Chua (ACM Trans. Knowl. Discov. Data, 2024)

Causal Inference in Recommender Systems: A Survey and Future Directions. - Chen Gao 001; Yu Zheng 010; Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Yong Li 008 (ACM Trans. Inf. Syst., 2024)

Revisiting Attack-Caused Structural Distribution Shift in Graph Anomaly Detection. - Yuan Gao 020; Jinghan Li; Xiang Wang 010; Xiangnan He 001; Huamin Feng; Yongdong Zhang 001 (IEEE Trans. Knowl. Data Eng., 2024)

Mitigating Hidden Confounding Effects for Causal Recommendation. - Xinyuan Zhu; Yang Zhang 072; Fuli Feng; Xun Yang 001; Dingxian Wang; Xiangnan He 001 (IEEE Trans. Knowl. Data Eng., 2024)

How graph convolutions amplify popularity bias for recommendation? - Jiajia Chen; Jiancan Wu; Jiawei Chen 007; Xin Xin 003; Yong Li 008; Xiangnan He 001 (Frontiers Comput. Sci., 2024)

Inductive Lottery Ticket Learning for Graph Neural Networks. - Yongduo Sui; Xiang Wang 010; Tianlong Chen 001; Meng Wang 001; Xiangnan He 001; Tat-Seng Chua (J. Comput. Sci. Technol., 2024)

HoGRN: Explainable Sparse Knowledge Graph Completion via High-Order Graph Reasoning Network. - Weijian Chen 001; Yixin Cao 002; Fuli Feng; Xiangnan He 001; Yongdong Zhang 001 (IEEE Trans. Knowl. Data Eng., 2024)

Customizing In-context Learning for Dynamic Interest Adaption in LLM-based Recommendation. - Keqin Bao; Ming Yan; Yang Zhang 072; Jizhi Zhang; Wenjie Wang 007; Fuli Feng; Xiangnan He 001 (ACL (Findings), 2025)

Personalized Generation In Large Model Era: A Survey. - Yiyan Xu; Jinghao Zhang; Alireza Salemi; Xinting Hu; Wenjie Wang 007; Fuli Feng; Hamed Zamani; Xiangnan He 001; Tat-Seng Chua (ACL (1), 2025)

Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters. - Yuan Wang; Ouxiang Li; Tingting Mu; Yanbin Hao; Kuien Liu; Xiang Wang 010; Xiangnan He 001 (CVPR, 2025)

Unified Parameter-Efficient Unlearning for LLMs. - Chenlu Ding; Jiancan Wu; Yancheng Yuan; Jinda Lu; Kai Zhang 038; Alex Su; Xiang Wang 010; Xiangnan He 001 (ICLR, 2025)

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models. - Junfeng Fang; Houcheng Jiang; Kun Wang 056; Yunshan Ma; Jie Shi; Xiang Wang 010; Xiangnan He 001; Tat-Seng Chua (ICLR, 2025)

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. - Junkang Wu; Yuexiang Xie; Zhengyi Yang 007; Jiancan Wu; Jiawei Chen 007; Jinyang Gao; Bolin Ding; Xiang Wang 010; Xiangnan He 001 (ICLR, 2025)

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation. - Shihao Cai; Jizhi Zhang; Keqin Bao; Chongming Gao; Qifan Wang 001; Fuli Feng; Xiangnan He 001 (SIGIR, 2025)

Process-Supervised LLM Recommenders via Flow-guided Tuning. - Chongming Gao; Mengyao Gao; Chenxiao Fan; Shuai Yuan 018; Wentao Shi 002; Xiangnan He 001 (SIGIR, 2025)

Multi-Grained Patch Training for Efficient LLM-based Recommendation. - Jiayi Liao; Ruobing Xie; Sihang Li 002; Xiang Wang 010; Xingwu Sun; Zhanhui Kang; Xiangnan He 001 (SIGIR, 2025)

Addressing Missing Data Issue for Diffusion-based Recommendation. - Wenyu Mao; Zhengyi Yang 007; Jiancan Wu; Haozhe Liu; Yancheng Yuan; Xiang Wang 010; Xiangnan He 001 (SIGIR, 2025)

Generative Recommendation: Towards Personalized Multimodal Content Generation. - Wenjie Wang 007; Xinyu Lin 001; Fuli Feng; Xiangnan He 001; Tat-Seng Chua (WWW (Companion Volume), 2025)

SPRec: Self-Play to Debias LLM-based Recommendation. - Chongming Gao; Ruijun Chen; Shuai Yuan 018; Kexin Huang; Yuanqing Yu; Xiangnan He 001 (WWW, 2025)

Personalized Image Generation with Large Multimodal Models. - Yiyan Xu; Wenjie Wang 007; Yang Zhang 072; Biao Tang; Peng Yan; Fuli Feng; Xiangnan He 001 (WWW, 2025)

The 3rd Workshop on Personal Intelligence with Generative AI. - Yang Zhang 072; Wenjie Wang 007; Xinyu Lin 001; Fuli Feng; Hongzhi Yin; Wayne Xin Zhao; Lina Yao 001; Yang Song 008; Xiangnan He 001 (WWW (Companion Volume), 2025)

Explainable and Efficient Editing for Large Language Models. - Tianyu Zhang; Junfeng Fang; Houcheng Jiang; Baolong Bi; Xiang Wang 010; Xiangnan He 001 (WWW, 2025)

A compact autonomous inspection system for greenhouse environmental information sensing and three-dimensional visualization. - Rui Yan; Xiangnan He 001; Zhen Wang; Yuting Wang; Zhemin Li; Xian Li (Comput. Electron. Agric., 2025)

Symmetric Hallucination With Knowledge Transfer for Few-Shot Learning. - Shuo Wang 008; Xinyu Zhang 017; Meng Wang 001; Xiangnan He 001 (IEEE Trans. Multim., 2025)

PatchRec: Multi-Grained Patching for Efficient LLM-based Sequential Recommendation. - Jiayi Liao; Ruobing Xie; Sihang Li 002; Xiang Wang 010; Xingwu Sun; Zhanhui Kang; Xiangnan He 001 (CoRR, 2025)

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search. - Wentao Shi 002; Zichun Yu; Fuli Feng; Xiangnan He 001; Chenyan Xiong (CoRR, 2025)

Addressing Delayed Feedback in Conversion Rate Prediction via Influence Functions. - Chenlu Ding; Jiancan Wu; Yancheng Yuan; Junfeng Fang; Cunchun Li; Xiang Wang 010; Xiangnan He 001 (CoRR, 2025)

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs. - Jinda Lu; Junkang Wu; Jinghan Li; Xiaojun Jia; Shuo Wang 008; Yifan Zhang 004; Junfeng Fang; Xiang Wang 010; Xiangnan He 001 (CoRR, 2025)

Reason4Rec: Large Language Models for Recommendation with Deliberative User Preference Alignment. - Yi Fang 008; Wenjie Wang 007; Yang Zhang 072; Fengbin Zhu; Qifan Wang 001; Fuli Feng; Xiangnan He 001 (CoRR, 2025)

AnyEdit: Edit Any Knowledge Encoded in Language Models. - Houcheng Jiang; Junfeng Fang; Ningyu Zhang 001; Guojun Ma; Mingyang Wan; Xiang Wang 010; Xiangnan He 001; Tat-Seng Chua (CoRR, 2025)

Less is More: Improving LLM Alignment via Preference Data Selection. - Xun Deng; Han Zhong; Rui Ai 004; Fuli Feng; Zheng Wang 027; Xiangnan He 001 (CoRR, 2025)

A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance. - Yongduo Sui; Shuyao Wang; Jie Sun 030; Zhiyuan Liu 010; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010; Xiangnan He 001 (ACM Trans. Knowl. Discov. Data, 2025)

Larger or Smaller Reward Margins to Select Preferences for Alignment? - Kexin Huang; Junkang Wu; Ziqian Chen; Xue Wang 010; Jinyang Gao; Bolin Ding; Jiancan Wu; Xiangnan He 001; Xiang Wang 010 (CoRR, 2025)

Addressing Overprescribing Challenges: Fine-Tuning Large Language Models for Medication Recommendation Tasks. - Zihao Zhao 004; Chenxiao Fan; Chongming Gao; Fuli Feng; Xiangnan He 001 (CoRR, 2025)

RePO: ReLU-based Preference Optimization. - Junkang Wu; Kexin Huang; Xue Wang 010; Jinyang Gao; Bolin Ding; Jiancan Wu; Xiangnan He 001; Xiang Wang 010 (CoRR, 2025)

Route Sparse Autoencoder to Interpret Large Language Models. - Wei Shi; Sihang Li 002; Tao Liang; Mingyang Wan; Gojun Ma; Xiang Wang 010; Xiangnan He 001 (CoRR, 2025)

AdaViP: Aligning Multi-modal LLMs via Adaptive Vision-enhanced Preference Optimization. - Jinda Lu; Jinghan Li; Yuan Gao; Junkang Wu; Jiancan Wu; Xiang Wang 010; Xiangnan He 001 (CoRR, 2025)

Reinforced Latent Reasoning for LLM-based Recommendation. - Yang Zhang 072; Wenxin Xu; Xiaoyan Zhao 005; Wenjie Wang 007; Fuli Feng; Xiangnan He 001; Tat-Seng Chua (CoRR, 2025)

CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation. - Yang Zhang 072; Fuli Feng; Jizhi Zhang; Keqin Bao; Qifan Wang 001; Xiangnan He 001 (IEEE Trans. Knowl. Data Eng., 2025)

Reinforced Prompt Personalization for Recommendation with Large Language Models. - Wenyu Mao; Jiancan Wu; Weijian Chen 001; Chongming Gao; Xiang Wang 010; Xiangnan He 001 (ACM Trans. Inf. Syst., 2025)

Mitigating Safety Fallback in Editing-based Backdoor Injection on LLMs. - Houcheng Jiang; Zetong Zhao; Junfeng Fang; Haokai Ma; Ruipeng Wang; Yang Deng 002; Xiang Wang 010; Xiangnan He 001 (CoRR, 2025)

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning. - Shanle Zheng; Keqin Bao; Jizhi Zhang; Yang Zhang 072; Fuli Feng; Xiangnan He 001 (CoRR, 2025)

Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code. - Keqin Bao; Nuo Chen; Xiaoyuan Li; Binyuan Hui; Bowen Yu 002; Fuli Feng; Xiangnan He 001; Dayiheng Liu (CoRR, 2025)

Generative Multi-Target Cross-Domain Recommendation. - Jinqiu Jin; Yang Zhang 072; Fuli Feng; Xiangnan He 001 (CoRR, 2025)