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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
[j83]Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He:
How graph convolutions amplify popularity bias for recommendation? Frontiers Comput. Sci. 18(5): 185603 (2024)- [j82]Shuo Wang
, Jinda Lu, Haiyang Xu, Yanbin Hao, Xiangnan He:
Feature Mixture on Pre-Trained Model for Few-Shot Learning. IEEE Trans. Image Process. 33: 4104-4115 (2024) - [j81]Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua:
Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning. ACM Trans. Knowl. Discov. Data 18(5): 127:1-127:24 (2024) - [j80]Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He:
Mitigating Hidden Confounding Effects for Causal Recommendation. IEEE Trans. Knowl. Data Eng. 36(9): 4794-4805 (2024) - [j79]Yuan Gao, Jinghan Li, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang:
Revisiting Attack-Caused Structural Distribution Shift in Graph Anomaly Detection. IEEE Trans. Knowl. Data Eng. 36(9): 4849-4861 (2024) - [j78]Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi, Yongdong Zhang:
Causal Incremental Graph Convolution for Recommender System Retraining. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4718-4728 (2024) - [j77]Xun Deng, Fuli Feng, Xiang Wang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua:
Learning to Double-Check Model Prediction From a Causal Perspective. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5054-5063 (2024) - [j76]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) - [j75]Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li:
Causal Inference in Recommender Systems: A Survey and Future Directions. ACM Trans. Inf. Syst. 42(4): 88:1-88:32 (2024) - [c203]Jiayi Liao, Xu Chen, Qiang Fu, Lun Du, Xiangnan He, Xiang Wang, Shi Han, Dongmei Zhang:
Text-to-Image Generation for Abstract Concepts. AAAI 2024: 3360-3368 - [c202]Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu, Xiangnan He:
Boosting Few-Shot Learning via Attentive Feature Regularization. AAAI 2024: 7793-7801 - [c201]Yang Zhang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, Xiangnan He:
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation. ACL (1) 2024: 9181-9191 - [c200]Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian:
Towards 3D Molecule-Text Interpretation in Language Models. ICLR 2024 - [c199]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. ICLR 2024 - [c198]Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang:
A3S: A General Active Clustering Method with Pairwise Constraints. ICML 2024 - [c197]Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He:
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. SIGIR 2024: 448-457 - [c196]Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He:
Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. SIGIR 2024: 533-542 - [c195]Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He:
Diffusion Models for Generative Outfit Recommendation. SIGIR 2024: 1350-1359 - [c194]Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He:
LLaRA: Large Language-Recommendation Assistant. SIGIR 2024: 1785-1795 - [c193]Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng:
Large Language Models are Learnable Planners for Long-Term Recommendation. SIGIR 2024: 1893-1903 - [c192]Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He:
EXGC: Bridging Efficiency and Explainability in Graph Condensation. WWW 2024: 721-732 - [c191]Shuxian Bi, Wenjie Wang, Hang Pan, Fuli Feng, Xiangnan He:
Proactive Recommendation with Iterative Preference Guidance. WWW (Companion Volume) 2024: 871-874 - [c190]Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Large Language Models for Recommendation: Progresses and Future Directions. WWW (Companion Volume) 2024: 1268-1271 - [c189]Chen Gao, Fengli Xu, Xu Chen, Xiang Wang, Xiangnan He, Yong Li:
Simulating Human Society with Large Language Model Agents: City, Social Media, and Economic System. WWW (Companion Volume) 2024: 1290-1293 - [c188]Wenjie Wang, Yang Zhang, Xinyu Lin, Fuli Feng, Weiwen Liu, Yong Liu, Xiangyu Zhao, Wayne Xin Zhao, Yang Song, Xiangnan He:
The 2nd Workshop on Recommendation with Generative Models. WWW (Companion Volume) 2024: 1715-1718 - [c187]Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He:
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. WWW 2024: 3253-3264 - [c186]Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He:
Item-side Fairness of Large Language Model-based Recommendation System. WWW 2024: 4717-4726 - [i176]Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian:
Towards 3D Molecule-Text Interpretation in Language Models. CoRR abs/2401.13923 (2024) - [i175]Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang:
Alleviating Structural Distribution Shift in Graph Anomaly Detection. CoRR abs/2401.14155 (2024) - [i174]Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He:
EXGC: Bridging Efficiency and Explainability in Graph Condensation. CoRR abs/2402.05962 (2024) - [i173]Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He:
Item-side Fairness of Large Language Model-based Recommendation System. CoRR abs/2402.15215 (2024) - [i172]Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He:
DiFashion: Towards Personalized Outfit Generation and Recommendation. CoRR abs/2402.17279 (2024) - [i171]Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng:
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning. CoRR abs/2403.00843 (2024) - [i170]Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He:
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. CoRR abs/2403.00844 (2024) - [i169]Wenjie Wang, Yang Zhang, Xinyu Lin, Fuli Feng, Weiwen Liu, Yong Liu, Xiangyu Zhao, Wayne Xin Zhao, Yang Song, Xiangnan He:
The 2nd Workshop on Recommendation with Generative Models. CoRR abs/2403.04399 (2024) - [i168]Shuxian Bi, Wenjie Wang, Hang Pan, Fuli Feng, Xiangnan He:
Proactive Recommendation with Iterative Preference Guidance. CoRR abs/2403.07571 (2024) - [i167]Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu, Xiangnan He:
Boosting Few-Shot Learning via Attentive Feature Regularization. CoRR abs/2403.17025 (2024) - [i166]Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He:
Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. CoRR abs/2403.17745 (2024) - [i165]Zhicai Wang, Longhui Wei, Tan Wang, Heyu Chen, Yanbin Hao, Xiang Wang, Xiangnan He, Qi Tian:
Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model. CoRR abs/2403.19600 (2024) - [i164]Zhiyu Hu, Yang Zhang, Minghao Xiao, Wenjie Wang, Fuli Feng, Xiangnan He:
Exact and Efficient Unlearning for Large Language Model-based Recommendation. CoRR abs/2404.10327 (2024) - [i163]Yongqi Li, Xinyu Lin, Wenjie Wang, Fuli Feng, Liang Pang, Wenjie Li, Liqiang Nie, Xiangnan He, Tat-Seng Chua:
A Survey of Generative Search and Recommendation in the Era of Large Language Models. CoRR abs/2404.16924 (2024) - [i162]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. CoRR abs/2404.19620 (2024) - [i161]Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He:
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. CoRR abs/2405.01063 (2024) - [i160]Yang Zhang, Keqin Bao, Ming Yang, Wenjie Wang, Fuli Feng, Xiangnan He:
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation. CoRR abs/2406.03210 (2024) - [i159]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. CoRR abs/2407.07880 (2024) - [i158]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
β-DPO: Direct Preference Optimization with Dynamic β. CoRR abs/2407.08639 (2024) - [i157]Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang:
A3S: A General Active Clustering Method with Pairwise Constraints. CoRR abs/2407.10196 (2024) - [i156]Wenyu Mao, Jiancan Wu, Weijian Chen, Chongming Gao, Xiang Wang, Xiangnan He:
Reinforced Prompt Personalization for Recommendation with Large Language Models. CoRR abs/2407.17115 (2024) - [i155]Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He:
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation. CoRR abs/2408.10159 (2024) - 2023
- [j74]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. AI Open 4: 80-90 (2023) - [j73]Zeyu Yang, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, Xiangnan He:
Interactive active learning for fairness with partial group label. AI Open 4: 175-182 (2023) - [j72]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) - [j71]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) - [j70]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) - [j69]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) - [j68]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) - [j67]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) - [j66]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) - [j65]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) - [j64]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) - [j63]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) - [j62]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) - [j61]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) - [j60]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) - [j59]Bin Wu, Xiangnan He, Qi Zhang, Meng Wang, Yangdong Ye:
GCRec: Graph-Augmented Capsule Network for Next-Item Recommendation. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10164-10177 (2023) - [j58]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) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [j53]Chen Gao, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, Jianxin Chang, Depeng Jin, Xiangnan He, Yong Li:
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. Trans. Recomm. Syst. 1(1): 1-51 (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) - [c185]Changyi Xiao, Xiangnan He, Yixin Cao:
Knowledge Graph Embedding by Normalizing Flows. AAAI 2023: 4756-4764 - [c184]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 - [c183]Jiarui Yu, Haoran Li, Yanbin Hao, Jinmeng Wu, Tong Xu, Shuo Wang, Xiangnan He:
How Can Contrastive Pre-training Benefit Audio-Visual Segmentation? A Study from Supervised and Zero-shot Perspectives. BMVC 2023: 367-374 - [c182]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 - [c181]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 - [c180]Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He:
Attack Prompt Generation for Red Teaming and Defending Large Language Models. EMNLP (Findings) 2023: 2176-2189 - [c179]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 - [c178]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 - [c177]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 - [c176]Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, Xiangnan He:
Discriminative-Invariant Representation Learning for Unbiased Recommendation. IJCAI 2023: 2270-2278 - [c175]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 - [c174]Jinda Lu, Shuo Wang, Xinyu Zhang, Yanbin Hao, Xiangnan He:
Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning. ACM Multimedia 2023: 3569-3578 - [c173]Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He:
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis. NeurIPS 2023 - [c172]Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He:
Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. NeurIPS 2023 - [c171]Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu:
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. NeurIPS 2023 - [c170]Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He:
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. NeurIPS 2023 - [c169]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He:
Understanding Contrastive Learning via Distributionally Robust Optimization. NeurIPS 2023 - [c168]Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He:
Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. NeurIPS 2023 - [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, Wenjie Wang, 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 - [i154]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) - [i153]