何向南，中国科学技术大学教授、博导、大数据学院副院长，合肥综合性国家科学中心数据空间研究院副院长，安徽省人工智能学会副理事长。常年致力于信息检索与推荐、数据挖掘、机器学习等大数据与人工智能领域前沿研究，在CCF A类会议和期刊发表论文100余篇，如会议SIGIR、WWW、KDD等和期刊IEEE TKDE、ACM TOIS等，谷歌学术引用36000余次，Elsevier中国高被引学者，研究成果在多个商业公司的线上系统获得应用，取得积极效果。担任多个期刊的副主编，如IEEE Transactions on Knowledge and Data Engineering (TKDE)、IEEE Transactions on Big Data (TBD), ACM Transactions on Information Systems (TOIS)、ACM Transactions on Recommender Systems (TORS)等。主持多项国家级项目，如基金委重点项目，科技部重点研发计划课题等，入选2018年青年国家创新人才项目。 所获荣誉 2016年，SIGIR最佳论文提名奖 2018年，WWW最佳论文提名奖 2020年，阿里巴巴达摩院青橙奖（获奖理由：聚焦个性化推荐，为信息过载精准施策） 2021年，SIGIR最佳论文提名奖 2022年，教育部技术发明一等奖 2022年，AI 2000人工智能最具影响力学者“信息检索与推荐”领域排名第一 2023年，SIGIR最佳论文提名奖 2023年，国际基础科学大会前沿科学奖 2023年，安徽青年五四奖章

信息检索与推荐 数据挖掘与大数据 大模型与通用人工智能

β-DPO: Direct Preference Optimization with Dynamic β Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang& Xiangnan He* NeurIPS 2024 (Accept Rate: 25.8%)    Codes    *Corresponding Customizing Language Models with Instance-wise LoRA for Sequential Recommendation Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang & Xiangnan He* NeurIPS 2024 (Accept Rate: 25.8%)    *Corresponding Large Language Models are Learnable Planners for Long-Term Recommendation Wentao Shi, Xiangnan He*, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang & Fuli Feng SIGIR 2024 (Accept Rate: 20.1%)    Codes    *Corresponding Large Language-Recommendation Assistant Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang & Xiangnan He* SIGIR 2024 (Accept Rate: 20.1%)    Codes    *Corresponding Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao & Xiangnan He* SIGIR 2024 (Accept Rate: 20.1%)    Codes    *Corresponding Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng & Xiangnan He SIGIR 2024 (Accept Rate: 20.1%)    Codes    Diffusion Models for Generative Outfit Recommendation Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang & Xiangnan He SIGIR 2024 (Accept Rate: 20.1%)    Codes    Item-side Fairness of Large Language Model-based Recommendation System Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng & Xiangnan He* WWW 2024 (Accept Rate: 20.2%)    Codes    *Corresponding Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu & Xiangnan He* WWW 2024 (Accept Rate: 20.2%)    Codes    *Corresponding EXGC: Bridging Efficiency and Explainability in Graph Condensation Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang & Xiangnan He WWW 2024 (Accept Rate: 20.2%)    Codes    Proactive Recommendation with Iterative Preference Guidance Shuxian Bi, Wenjie Wang, Hang Pan, Fuli Feng & Xiangnan He WWW 2024 (Short)    Codes    Towards 3D Molecule-Text Interpretation in Language Models Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He*, Kenji Kawaguchi, Tat-Seng Chua & Qi Tian ICLR 2024 (Accept Rate: 31%)    Codes    *Corresponding Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference for Recommendation Haoxuan Li, Chunyuan Zheng, Sihao Ding, Fuli Feng, Xiangnan He, Zhi Geng & Peng Wu ICLR 2024 (Accept Rate: 31%)    Boosting Few-shot Learning via Attentive Feature Regularization Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu & Xiangnan He AAAI 2024 (Accept Rate: 23.75%)    Text-to-Image Generation for Abstract Concepts Jiayi Liao, Xu Chen, Qiang Fu, Lun Du, Xiangnan He, Xiang Wang, Shi Han & Dongmei Zhang AAAI 2024 (Accept Rate: 23.75%)    CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System Chongming Gao, Wenqiang Lei, Jiawei Chen, Siqi Wang, Xiangnan He*, Shijun Li, Biao Li, Yuan Zhang & Peng Jiang ACM Transactions on Information Systems (TOIS)    Codes    *Corresponding Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu & Xiangnan He* NeurIPS 2023 (Accept Rate: 26.1%)   Codes    *Corresponding Understanding Contrastive Learning via Distributionally Robust Optimization Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang & Xiangnan He* NeurIPS 2023 (Accept Rate: 26.1%)    Codes    *Corresponding Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis Junfeng Fang, Wei Liu, Xiang Wang, Zemin Liu, An Zhang, Yuan Gao & Xiangnan He* NeurIPS 2023 (Accept Rate: 26.1%)    Codes    *Corresponding Unleashing the Power of Graph Data Augmentation on Covariate Shift Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, JUN ZHOU, Xiang Wang & Xiangnan He* NeurIPS 2023 (Accept Rate: 26.1%)    Codes    *Corresponding Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan & Xiangnan He NeurIPS 2023 (Accept Rate: 26.1%)    Codes    TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng & Xiangnan He* Recsys 2023 (Accept Rate: 25.3%)    Codes    *Corresponding Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng & Xiangnan He* Recsys 2023 (Accept Rate: 25.3%)    Codes    *Corresponding RecAD: Towards A Unified Library for Recommender Attack and Defense Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng & Xiangnan He Recsys 2023 (Reproducibility)   Codes Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning Jinda Lu, Shuo Wang, XinYu Zhang, Yanbin Hao & Xiangnan He* ACM MM 2023 (Full, Accept Rate: 29.3%)    Codes    *Corresponding CgT-GAN: CLIP-guided Text GAN for Image Captioning Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu & Xiangnan He* ACM MM 2023 (Full, Accept Rate: 29.3%)    Codes    *Corresponding Counterfactual Active Learning for Out-of-Distribution Generalization Xun Deng, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He & Yong Liao ACL 2023 (Full)    Codes    Discriminative-Invariant Representation Learning for Unbiased Recommendation Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu & Xiangnan He IJCAI 2023 (Full, Accept Rate: 15%)    Codes    A Generic Learning Framework for Sequential Recommendation with Distribution Shifts Zhengyi Yang, Xiangnan He*, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen & Xiang Wang SIGIR 2023 (Full, Accept Rate: 20.1%)    Codes    *Corresponding Alleviating Matthew Effect of Offline Reinforcement Learning in Recommendation Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang & Xiangnan He* SIGIR 2023 (Full, Accept Rate: 20.1%)    Codes    *Corresponding    (Best Paper Honorable Mention) Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He* & Yongdong Zhang SIGIR 2023 (Full, Accept Rate: 20.1%)    Codes    *Corresponding Diffusion Recommender Model Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He & Tat-Seng Chua SIGIR 2023 (Full, Accept Rate: 20.1%)    Codes    Bi-directional Distribution Alignment for Transductive Zero Shot Learning Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang & Xiangnan He* CVPR 2023 (Full)    Codes    *Corresponding Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum Yuan Gao, Xiang Wang, Xiangnan He*, Zhenguang Liu, Huamin Feng & Yongdong Zhang WWW 2023 (Full, Accept Rate: 19.2%)    Codes    *Corresponding On the Theories Behind Hard Negative Sampling for Recommendation Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao & Xiangnan He* WWW 2023 (Full, Accept Rate: 19.2%)    Codes    *Corresponding GIF: A General Graph Unlearning Strategy via Influence Function Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang & Xiangnan He* WWW 2023 (Full, Accept Rate: 19.2%)    Codes    *Corresponding Adap-τ: Adaptively Modulating Embedding Magnitude for Recommendation Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou & Xiangnan He* WWW 2023 (Full, Accept Rate: 19.2%)    Codes    *Corresponding Knowledge Graph Embedding by Normalizing Flows Changyi Xiao, Xiangnan He* & Yixin Cao AAAI 2023 (Full)    Codes    *Corresponding Unbiased Knowledge Distillation for Recommendation Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou & Xiangnan He* WSDM 2023 (Full, Accept Rate: 17.8%)    Codes    *Corresponding Alleviating Structural Distribution Shift in Graph Anomaly Detection Yuan Gao, Xiang Wang, Xiangnan He*, Zhenguang Liu, Huamin Feng & Yongdong Zhang WSDM 2023 (Full, Accept Rate: 17.8%)    Codes    *Corresponding Cooperative Explanations of Graph Neural Networks Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He & Tat-Seng Chua WSDM 2023 (Full, Accept Rate: 17.8%)    Codes    Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation Chenxu Wang, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu & Xiangnan He* IEEE Transactions on Big Data (TBD 2023)    Codes *Corresponding Learning to Double-check Model Prediction from a Causal Perspective Xun Deng, Fuli Feng, Xiang Wang, Xiangnan He, Hanwang Zhang & Tat-Seng Chua IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2023)    Codes Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He*, Xuezhi Cao, Fuzheng Zhang & Wei Wu IEEE Transactions on Knowledge and Data Engineering (TKDE 2023)    Codes   *Corresponding Causal Inference in Recommender Systems: A Survey and Future Directions Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He & Yong Li ACM Transactions on Information Systems (TOIS 2023)    Inductive Lottery Ticket Learning for Graph Neural Networks Yongduo Sui, Xiang Wang, Tianlong Chen, Meng Wang, & Xiangnan He* & Tat-Seng Chua Journal of Computer Science and Technology (JCST)    Codes    *Corresponding Addressing Confounding Feature Issue for Causal Recommendation Xiangnan He, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling & Yongdong Zhang ACM Transactions on Information Systems (TOIS 2022)    Codes    KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao & Tat-Seng Chua CIKM 2022 (Full Research)    Dataset Link, Codes    KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang & Xiangnan He CIKM 2022 (Resource Track)    Dataset Link    Multi-directional Knowledge Transfer for Few-Shot Learning Shuo Wang, Xinyu Zhang, Yanbin Hao, Chengbing Wang & Xiangnan He* ACM MM 2022 (Full, Accept Rate: 27.9%)    Codes    *Corresponding Hierarchical Hourglass Convolutional Network for Efficient Video Classification Yi Tan, Yanbin Hao*, Hao Zhang, Shou Wang & Xiangnan He* ACM MM 2022 (Full, Accept Rate: 27.9%)    Codes    *Corresponding Parameterization of Cross-Token Relations with Relative Positional Encoding for Vision MLP Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu & Xiangnan He ACM MM 2022 (Full, Accept Rate: 27.9%)    Codes    Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation Yanbin Hao, Jingru Duan, Hao Zhang, Bin Zhu, Pengyuan Zhou & Xiangnan He ACM MM 2022 (Full, Accept Rate: 27.9%)    Codes    Invariant Representation Learning for Multimedia Recommendation Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He & Jinhui Tang ACM MM 2022 (Full, Accept Rate: 27.9%)    Codes    Causal Attention for Interpretable and Generalizable Graph Classification Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He & Tat-Seng Chua KDD 2022 (Full Research, Accept Rate: 15%)    Codes    Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao & Yongdong Zhang KDD 2022 (Full Research, Accept Rate: 15%)    Codes    Let Invariant Rationale Discovery Inspire Graph Contrastive Learning Sihang Li, Xiang Wang*, An Zhang, Ying-Xin Wu, Xiangnan He* & Tat-Seng Chua ICML 2022 (Full, Accept Rate: 21.9%)    Codes    *Corresponding Reinforced Causal Explainer for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He & Tat-Seng Chua IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)    Codes    Interpolative Distillation for Unifying Biased and Debiased Recommendation Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao & Yongdong Zhang SIGIR 2022 (Full, Accept rate: 20%)    Codes    Group Contextualization for Video Recognition Yanbin Hao, Hao Zhang, Chong-Wah Ngo & Xiangnan He CVPR 2022 (Full, Accept rate: 25.3%)    Codes    Discovering Invariant Rationales for Graph Neural Networks Ying-Xin Wu, Xiang Wang, An Zhang, Xiangnan He & Tat-Seng Chua ICLR 2022    Codes    Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu & Tat-Seng Chua ACL 2022 (Full, main conference)    Codes    Cross Pairwise Ranking for Unbiased Item Recommendation Qi Wan, Xiangnan He*, Xiang Wang, Jiancan Wu, Wei Guo & Ruiming Tang WWW 2022 (Full, Accept rate: 17.7%)    Codes    *Corresponding author Causal Representation Learning for Out-of-Distribution Recommendation Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Min Lin & Tat-Seng Chua WWW 2022 (Full, Accept rate: 17.7%)    Codes    Learning Robust Recommenders through Cross-Model Agreement Yu Wang, Xin Xin, Zaiqiao Meng, Jeoman Jose, Fuli Feng & Xiangnan He WWW 2022 (Full, Accept rate: 17.7%)    Codes    Interactive Hypergraph Neural Network for Personalized Product Search Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng & Xiangnan He WWW 2022 (Full, Accept rate: 17.7%)    Codes    Bias and Debias in Recommender System: A Survey and Future Directions Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang & Xiangnan He* ACM Transactions on Information Systems (TOIS 2022)    Slides   *Corresponding Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions Chen Gao, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, Jianxin Chang, Depeng Jin, Xiangnan He & Yong Li ACM Transactions on Recommender Systems (TORS 2022)    Attention in Attention: Modeling Context Correlation for Efficient Video Classification Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu & Xiangnan He IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)    Codes Rumor Detection with Self-supervised Learning on Texts and Social Graph Yuan Gao, Xiang Wang*, Xiangnan He*, Huamin Feng & Yongdong Zhang Frontiers of Computer Science (FOCS)    *Corresponding Time-aware Path Reasoning on Knowledge Graph for Recommendation Yuyue Zhao, Xiang Wang, Jiawei Chen, Wei Tang, Yashen Wang, Xiangnan He & Haiyong Xie ACM Transactions on Information Systems (TOIS 2022)    Codes A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation Le Wu, Xiangnan He, Xiang Wang, Kun Zhang & Meng Wang IEEE Transactions on Knowledge and Data Engineering (TKDE 2022) Causal Incremental Graph Convolution for Recommender System Retraining Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi & Yongdong Zhang IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2022)    Codes GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He & Jun Liu IEEE Transactions on Knowledge and Data Engineering (TKDE 2022)    Codes CatGCN: Graph Convolutional Networks with Categorical Node Features Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling & Yongdong Zhang IEEE Transactions on Knowledge and Data Engineering (TKDE 2022)    Codes Exploring Lottery Ticket Hypothesis in Media Recommender Systems Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu & Xiangnan He* International Journal of Intelligent Systems (IJIS 2022)    Codes    *Corresponding Graph Convolution Machine for Context-aware Recommender System Jiancan Wu, Xiangnan He*, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian & Xing Xie Frontiers of Computer Science (FOCS 2022)    Codes *Corresponding author Advances and Challenges in Conversational Recommender Systems: A Survey Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke & Tat-Seng Chua AI Open    Slides Towards Multi-Grained Explainability for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He* & Tat-Seng Chua NeurIPS 2021 (Full, Accept rate: 26%)    Codes   Slides *Corresponding author DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu & Xiangnan He CIKM 2021 (Full, Accept rate: 21.3%)    Codes   Slides A Deep Learning Framework for Self-evolving Hierarchical Community Detection Daizong Ding, Mi Zhang, Hanrui Wang, Xudong Pan, Min Yang & Xiangnan He CIKM 2021 (Full, Accept rate: 21.3%)    Slides Selective Dependency Aggregation for Action Classification Yi Tan, Yanbin Hao, Xiangnan He, Yinwei Wei & Xun Yang MM 2021 (Full, Accept rate: 28%)    Codes    Slides Causal Intervention for Leveraging Popularity Bias in Recommendation Yang Zhang, Fuli Feng*, Xiangnan He*, Tianxin Wei, Chonggang Song, Guohui Ling & Yongdong Zhang SIGIR 2021 (Full, Accept rate: 21%)    Codes    Slides *Corresponding    (Best Paper Honorable Mention) AutoDebias: Learning to Debias for Recommendation Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He*, Xin Xin, Liang Chen, Guli Lin & Keping Yang SIGIR 2021 (Full, Accept rate: 21%)    Codes    Slides *Corresponding author Self-supervised Graph Learning for Recommendation Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian & Xing Xie SIGIR 2021 (Full, Accept rate: 21%)    Codes    Slides Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang & Tat-Seng Chua SIGIR 2021 (Full, Accept rate: 21%)    Codes    Slides Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method Fuli Feng, Weiran Huang, Xin Xin, Xiangnan He, Tat-Seng Chua & Qifan Wang SIGIR 2021 (Full, Accept rate: 21%)    Codes    Slides Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System Tianxin Wei, Fuli Feng*, Jiawei Chen, Ziwei Wu, Jinfeng Yi & Xiangnan He* KDD 2021 (Full, Accept rate: 15.4%)    Codes    Slides *Corresponding author Deconfounded Recommendation for Alleviating Bias Amplification Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang & Tat-Seng Chua KDD 2021 (Full, Accept rate: 15.4%)    Codes    Slides On the Equivalence of Decoupled Graph Convolution Network and Label Propagation Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding & Peng Cui WWW 2021 (Full, Accept rate: 20.6%)    Codes    Slides Disentangling User Interest and Conformity for Recommendation with Causal Embedding Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li & Depeng Jin WWW 2021 (Full, Accept rate: 20.6%)    Codes    Slides Learning Intents behind Interactions with Knowledge Graph for Recommendation Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He* & Tat-Seng Chua WWW 2021 (Full, Accept rate: 20.6%)    Codes    Slides *Corresponding author Denoising Implicit Feedback for Recommendation Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie & Tat-Seng Chua WSDM 2021 (Full, Accept rate: 18.6%)    Codes    Slides Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users Shijun Li, Wenqiang Lei, Qingyun Wu, Xiangnan He, Peng Jiang & Tat-Seng Chua ACM Transactions on Information Systems (TOIS 2021)    Codes Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions Fuli Feng, Xiangnan He*, Hanwang Zhang & Tat-Seng Chua IEEE Transactions on Knowledge and Data Engineering (TKDE 2021)    Codes *Corresponding author Adversarial Attack on Large Scale Graph Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He & Zibin Zeng IEEE Transactions on Knowledge and Data Engineering (TKDE 2021)    Codes Structure-Enhanced Meta-Learning For Few-Shot Graph Classification Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li & Xiangnan He AI Open    Codes Deep Learning for Matching in Search and Recommendation Jun Xu, Xiangnan He & Hang Li Foundations and Trends in Information Retrieval (FNTIR 2020)    Slides LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang & Meng Wang SIGIR 2020 (Full, Accept rate: 26%)    Codes    Slides How to Retrain Recommender System? A Sequential Meta-Learning Approach Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li & Yongdong Zhang SIGIR 2020 (Full, Accept rate: 26%)    Codes    Slides Bundle Recommendation with Graph Convolutional Networks Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin & Yong Li SIGIR 2020 (Short)    Codes    (Best Short Paper Honorable Mention) Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation Fajie Yuan, Xiangnan He, Alexandros Karatzoglou & Liguang Zhang SIGIR 2020 (Full, Accept rate: 26%)    Codes Interactive Path Reasoning on Graph for Conversational Recommendation Wenqiang Lei, Gangyi Zhang, Xiangnan He*, Yisong Miao, Xiang Wang, Liang Chen & Tat-Seng Chua KDD 2020 (Full, Accept rate: 16.9%)    Codes Corresponding author Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems Wenqiang Lei, Xiangnan He*, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan & Tat-Seng Chua WSDM 2020 (Full, Accept rate: 15%)    Slides    Data & Codes *Corresponding author Reinforced Negative Sampling over Knowledge Graph for Recommendation Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Weng Wang & Tat-Seng Chua WWW 2020 (Full, Accept rate: 19%)    Codes Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation Fajie Yuan, Xiangnan He, Haochuan Jiang, Guibing Guo, Jian Xiong, Zhezhao Xu & Xiong Yilin WWW 2020 (Full, Accept rate: 19%)    Codes    Slides Bilinear Graph Neural Network with Neighbor Interactions Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng & Yongdong Zhang IJCAI 2020 (Full, Accept rate: 12.6%)    Codes Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning Daizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan He AAAI 2020 (Full, Accept rate: 20.6%)    Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure Fuli Feng, Xiangnan He*, Jie Tang & Tat-Seng Chua IEEE Transactions on Knowledge and Data Engineering (TKDE 2020)    Codes *Corresponding author