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ORCIDXiangnan He 0001
Person information
- affiliation: University of Science and Technology of China, School of Information Science and Technology, Hefei, China
- affiliation (PhD 2016): National University of Singapore, School of Computing, Singapore
Other persons with the same name
- Xiangnan He 0002 — Fudan University, Shanghai, China
- Xiangnan He 0003 — Southern University of Science and Technology, Shenzhen, China
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2020 – today
- 2024
[j71]Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang:
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System. ACM Trans. Inf. Syst. 42(1): 14:1-14:27 (2024)- 2023
- [j70]Yuan Gao
, Xiang Wang, Xiangnan He, Huamin Feng, Yong-Dong Zhang:
Rumor detection with self-supervised learning on texts and social graph. Frontiers Comput. Sci. 17(4): 174611 (2023) - [j69]Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Reinforced Causal Explainer for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2297-2309 (2023) - [j68]Chenxu Wang, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu, Xiangnan He:
Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation. IEEE Trans. Big Data 9(6): 1607-1619 (2023) - [j67]Kang Liu, Feng Xue, Xiangnan He, Dan Guo, Richang Hong:
Joint Multi-Grained Popularity-Aware Graph Convolution Collaborative Filtering for Recommendation. IEEE Trans. Comput. Soc. Syst. 10(1): 72-83 (2023) - [j66]Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng:
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35(1): 82-95 (2023) - [j65]Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua:
Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions. IEEE Trans. Knowl. Data Eng. 35(1): 225-236 (2023) - [j64]Yu Zheng, Chen Gao, Xiangnan He, Depeng Jin, Yong Li:
Incorporating Price into Recommendation With Graph Convolutional Networks. IEEE Trans. Knowl. Data Eng. 35(2): 1609-1623 (2023) - [j63]Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin, Yong Li:
Bundle Recommendation and Generation With Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2326-2340 (2023) - [j62]Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang:
User-Specific Adaptive Fine-Tuning for Cross-Domain Recommendations. IEEE Trans. Knowl. Data Eng. 35(3): 3239-3252 (2023) - [j61]Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, Yongdong Zhang:
CatGCN: Graph Convolutional Networks With Categorical Node Features. IEEE Trans. Knowl. Data Eng. 35(4): 3500-3511 (2023) - [j60]Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang:
A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4425-4445 (2023) - [j59]Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu:
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4813-4824 (2023) - [j58]Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu:
Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation. IEEE Trans. Knowl. Data Eng. 35(10): 9920-9931 (2023) - [j57]Yuyue Zhao, Xiang Wang, Jiawei Chen, Yashen Wang, Wei Tang, Xiangnan He, Haiyong Xie:
Time-aware Path Reasoning on Knowledge Graph for Recommendation. ACM Trans. Inf. Syst. 41(2): 26:1-26:26 (2023) - [j56]Xiangnan He, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling, Yongdong Zhang:
Addressing Confounding Feature Issue for Causal Recommendation. ACM Trans. Inf. Syst. 41(3): 53:1-53:23 (2023) - [j55]Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, Xiangnan He:
Bias and Debias in Recommender System: A Survey and Future Directions. ACM Trans. Inf. Syst. 41(3): 67:1-67:39 (2023) - [j54]Honglei Zhang, Fangyuan Luo, Jun Wu, Xiangnan He, Yidong Li:
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization. ACM Trans. Inf. Syst. 41(4): 90:1-90:28 (2023) - [j53]Shuo Wang, Huixia Ben, Yanbin Hao, Xiangnan He, Meng Wang:
Boosting Hyperspectral Image Classification with Dual Hierarchical Learning. ACM Trans. Multim. Comput. Commun. Appl. 19(1): 21:1-21:19 (2023) - [j52]Bin Wu, Xiangnan He, Le Wu, Xue Zhang, Yangdong Ye:
Graph-Augmented Co-Attention Model for Socio-Sequential Recommendation. IEEE Trans. Syst. Man Cybern. Syst. 53(7): 4039-4051 (2023) - [c176]Changyi Xiao, Xiangnan He, Yixin Cao:
Knowledge Graph Embedding by Normalizing Flows. AAAI 2023: 4756-4764 - [c175]Xun Deng, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He, Yong Liao:
Counterfactual Active Learning for Out-of-Distribution Generalization. ACL (1) 2023: 11362-11377 - [c174]Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun:
The 1st Workshop on Recommendation with Generative Models. CIKM 2023: 5300-5303 - [c173]Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He:
Bi-Directional Distribution Alignment for Transductive Zero-Shot Learning. CVPR 2023: 19893-19902 - [c172]Meng Jiang, Yang Zhang, Yuan Gao, Yansong Wang, Fuli Feng, Xiangnan He:
LightMIRM: Light Meta-learned Invariant Risk Minimization for Trustworthy Loan Default Prediction. ICDE 2023: 3494-3507 - [c171]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation (Extended Abstract). ICDE 2023: 3821-3822 - [c170]Bin Wu, Xiangnan He, Yu Chen, Liqiang Nie, Kai Zheng, Yangdong Ye:
Modeling Product's Visual and Functional Characteristics for Recommender Systems (Extended Abstract). ICDE 2023: 3837-3838 - [c169]Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, Xiangnan He:
Discriminative-Invariant Representation Learning for Unbiased Recommendation. IJCAI 2023: 2270-2278 - [c168]Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He:
CgT-GAN: CLIP-guided Text GAN for Image Captioning. ACM Multimedia 2023: 2252-2263 - [c167]Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng, Xiangnan He:
RecAD: Towards A Unified Library for Recommender Attack and Defense. RecSys 2023: 234-244 - [c166]Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou:
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. RecSys 2023: 682-687 - [c165]Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. RecSys 2023: 993-999 - [c164]Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. RecSys 2023: 1007-1014 - [c163]Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang, Xiangnan He:
Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation. SIGIR 2023: 238-248 - [c162]Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang:
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. SIGIR 2023: 331-340 - [c161]Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua:
Diffusion Recommender Model. SIGIR 2023: 832-841 - [c160]Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang:
Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation. SIGIR 2023: 1386-1395 - [c159]Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He:
Causal Recommendation: Progresses and Future Directions. SIGIR 2023: 3432-3435 - [c158]Keqin Bao, Jizhi Zhang, Yang Zhang, Wang Wenjie, Fuli Feng, Xiangnan He:
Large Language Models for Recommendation: Progresses and Future Directions. SIGIR-AP 2023: 306-309 - [c157]Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang:
Alleviating Structural Distribution Shift in Graph Anomaly Detection. WSDM 2023: 357-365 - [c156]Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua:
Cooperative Explanations of Graph Neural Networks. WSDM 2023: 616-624 - [c155]Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He:
Unbiased Knowledge Distillation for Recommendation. WSDM 2023: 976-984 - [c154]Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He:
GIF: A General Graph Unlearning Strategy via Influence Function. WWW 2023: 651-661 - [c153]Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He:
On the Theories Behind Hard Negative Sampling for Recommendation. WWW 2023: 812-822 - [c152]Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He:
Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. WWW 2023: 1085-1096 - [c151]Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang:
Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum. WWW 2023: 1528-1538 - [i152]Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He:
On the Theories Behind Hard Negative Sampling for Recommendation. CoRR abs/2302.03472 (2023) - [i151]Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He:
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion. CoRR abs/2302.04088 (2023) - [i150]Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao:
Weakly Supervised Anomaly Detection: A Survey. CoRR abs/2302.04549 (2023) - [i149]Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He:
Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation. CoRR abs/2302.04775 (2023) - [i148]Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie:
Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors. CoRR abs/2302.08975 (2023) - [i147]Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He:
Bi-directional Distribution Alignment for Transductive Zero-Shot Learning. CoRR abs/2303.08698 (2023) - [i146]Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He:
GIF: A General Graph Unlearning Strategy via Influence Function. CoRR abs/2304.02835 (2023) - [i145]Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Generative Recommendation: Towards Next-generation Recommender Paradigm. CoRR abs/2304.03516 (2023) - [i144]Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua:
Diffusion Recommender Model. CoRR abs/2304.04971 (2023) - [i143]Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang:
Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation. CoRR abs/2304.13643 (2023) - [i142]Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. CoRR abs/2305.00447 (2023) - [i141]Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. CoRR abs/2305.07609 (2023) - [i140]Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He:
How Graph Convolutions Amplify Popularity Bias for Recommendation? CoRR abs/2305.14886 (2023) - [i139]Gangyi Zhang, Chongming Gao, Wenqiang Lei, Xiaojie Guo, Shijun Li, Lingfei Wu, Hongshen Chen, Zhuozhi Ding, Sulong Xu, Xiangnan He:
Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation. CoRR abs/2306.04487 (2023) - [i138]Yang Zhang, Zhiyu Hu, Yimeng Bai, Fuli Feng, Jiancan Wu, Qifan Wang, Xiangnan He:
Recommendation Unlearning via Influence Function. CoRR abs/2307.02147 (2023) - [i137]Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang, Xiangnan He:
Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation. CoRR abs/2307.04571 (2023) - [i136]Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu:
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community. CoRR abs/2307.09751 (2023) - [i135]Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou:
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. CoRR abs/2308.02571 (2023) - [i134]Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yancheng Luo, Fuli Feng, Xiangnan He, Qi Tian:
A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems. CoRR abs/2308.08434 (2023) - [i133]Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He:
CgT-GAN: CLIP-guided Text GAN for Image Captioning. CoRR abs/2308.12045 (2023) - [i132]Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon M. Jose, Fuli Feng:
Label Denoising through Cross-Model Agreement. CoRR abs/2308.13976 (2023) - [i131]Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng, Xiangnan He:
RecAD: Towards A Unified Library for Recommender Attack and Defense. CoRR abs/2309.04884 (2023) - [i130]Yi Tan, Zhaofan Qiu, Yanbin Hao, Ting Yao, Xiangnan He, Tao Mei:
Selective Volume Mixup for Video Action Recognition. CoRR abs/2309.09534 (2023) - [i129]Jiayi Liao, Xu Chen, Qiang Fu, Lun Du, Xiangnan He, Xiang Wang, Shi Han, Dongmei Zhang:
Text-to-Image Generation for Abstract Concepts. CoRR abs/2309.14623 (2023) - [i128]Yongxin Ni, Yu Cheng, Xiangyan Liu, Junchen Fu, Youhua Li, Xiangnan He, Yongfeng Zhang, Fajie Yuan:
A Content-Driven Micro-Video Recommendation Dataset at Scale. CoRR abs/2309.15379 (2023) - [i127]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He:
Understanding Contrastive Learning via Distributionally Robust Optimization. CoRR abs/2310.11048 (2023) - [i126]Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He:
Attack Prompt Generation for Red Teaming and Defending Large Language Models. CoRR abs/2310.12505 (2023) - [i125]Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang:
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation. CoRR abs/2310.16566 (2023) - [i124]Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, Xiangnan He:
CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation. CoRR abs/2310.19488 (2023) - [i123]Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He:
Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. CoRR abs/2310.20453 (2023) - [i122]Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He:
Large Language Model Can Interpret Latent Space of Sequential Recommender. CoRR abs/2310.20487 (2023) - 2022
- [j51]Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie:
Graph convolution machine for context-aware recommender system. Frontiers Comput. Sci. 16(6): 166614 (2022) - [j50]Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He:
Exploring lottery ticket hypothesis in media recommender systems. Int. J. Intell. Syst. 37(5): 3006-3024 (2022) - [j49]Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He, Hanwang Zhang:
Learning to Compose and Reason with Language Tree Structures for Visual Grounding. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 684-696 (2022) - [j48]Yuanyuan Jin, Wendi Ji, Wei Zhang, Xiangnan He, Xinyu Wang, Xiaoling Wang:
A KG-Enhanced Multi-Graph Neural Network for Attentive Herb Recommendation. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2560-2571 (2022) - [j47]Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He:
Attention in Attention: Modeling Context Correlation for Efficient Video Classification. IEEE Trans. Circuits Syst. Video Technol. 32(10): 7120-7132 (2022) - [j46]Yanbin Hao, Shuo Wang, Yi Tan, Xiangnan He, Zhenguang Liu, Meng Wang:
Spatio-Temporal Collaborative Module for Efficient Action Recognition. IEEE Trans. Image Process. 31: 7279-7291 (2022) - [j45]Chen Gao, Yong Li, Fuli Feng, Xiangning Chen, Kai Zhao, Xiangnan He, Depeng Jin:
Cross-domain Recommendation with Bridge-Item Embeddings. ACM Trans. Knowl. Discov. Data 16(1): 2:1-2:23 (2022) - [j44]Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou:
Learning Vertex Representations for Bipartite Networks. IEEE Trans. Knowl. Data Eng. 34(1): 379-393 (2022) - [j43]Bin Wu, Xiangnan He, Yun Chen, Liqiang Nie, Kai Zheng, Yangdong Ye:
Modeling Product's Visual and Functional Characteristics for Recommender Systems. IEEE Trans. Knowl. Data Eng. 34(3): 1330-1343 (2022) - [j42]Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu:
A Survey on Large-Scale Machine Learning. IEEE Trans. Knowl. Data Eng. 34(6): 2574-2594 (2022) - [j41]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34(9): 4385-4397 (2022) - [j40]Yinwei Wei, Xiang Wang, Xiangnan He, Liqiang Nie, Yong Rui, Tat-Seng Chua:
Hierarchical User Intent Graph Network for Multimedia Recommendation. IEEE Trans. Multim. 24: 2701-2712 (2022) - [j39]Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua:
Graph Technologies for User Modeling and Recommendation: Introduction to the Special Issue - Part 1. ACM Trans. Inf. Syst. 40(2): 21:1-21:5 (2022) - [j38]Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua:
Introduction to the Special Section on Graph Technologies for User Modeling and Recommendation, Part 2. ACM Trans. Inf. Syst. 40(3): 42:1-42:5 (2022) - [c150]Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu, Tat-Seng Chua:
Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning. ACL (1) 2022: 57-69 - [c149]Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, Tat-Seng Chua:
KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems. CIKM 2022: 540-550 - [c148]Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, Xiangnan He:
KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos. CIKM 2022: 3953-3957 - [c147]Chao Huang, Lianghao Xia, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommendation. CIKM 2022: 5136-5139 - [c146]Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Xiangnan He:
Group Contextualization for Video Recognition. CVPR 2022: 918-928 - [c145]Chuhan Wu, Fangzhao Wu, Xiangnan He, Yongfeng Huang:
DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning. EMNLP (Findings) 2022: 2933-2938 - [c144]Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua:
Discovering Invariant Rationales for Graph Neural Networks. ICLR 2022 - [c143]Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua:
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. ICML 2022: 13052-13065 - [c142]Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang:
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. KDD 2022: 305-315 - [c141]Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua:
Causal Attention for Interpretable and Generalizable Graph Classification. KDD 2022: 1696-1705 - [c140]Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, Jinhui Tang:
Invariant Representation Learning for Multimedia Recommendation. ACM Multimedia 2022: 619-628 - [c139]Yanbin Hao, Jingru Duan, Hao Zhang, Bin Zhu, Pengyuan Zhou, Xiangnan He:
Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation. ACM Multimedia 2022: 3754-3763 - [c138]Shuo Wang, Xinyu Zhang, Yanbin Hao, Chengbing Wang, Xiangnan He:
Multi-directional Knowledge Transfer for Few-Shot Learning. ACM Multimedia 2022: 3993-4002 - [c137]Yi Tan, Yanbin Hao, Hao Zhang, Shuo Wang, Xiangnan He:
Hierarchical Hourglass Convolutional Network for Efficient Video Classification. ACM Multimedia 2022: 5880-5891 - [c136]Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He:
Parameterization of Cross-token Relations with Relative Positional Encoding for Vision MLP. ACM Multimedia 2022: 6288-6299 - [c135]Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao, Yongdong Zhang:
Interpolative Distillation for Unifying Biased and Debiased Recommendation. SIGIR 2022: 40-49 - [c134]Chao Huang, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommender System. SIGIR 2022: 3440-3443 - [c133]Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie:
Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task. WMT 2022: 597-605 - [c132]