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Yingqiang Ge (葛英强)
Yingqiang Ge (葛英强)
Applied Scientist, Amazon
Verified email at amazon.com - Homepage
Title
Cited by
Cited by
Year
Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5)
S Geng, S Liu, Z Fu, Y Ge, Y Zhang
Proceedings of the 16th ACM Conference on Recommender Systems, 299-315, 2022
2692022
User-oriented fairness in recommendation
Y Li, H Chen, Z Fu, Y Ge, Y Zhang
Proceedings of the web conference 2021, 624-632, 2021
2142021
Fairness-aware explainable recommendation over knowledge graphs
Z Fu, Y Xian, R Gao, J Zhao, Q Huang, Y Ge, S Xu, S Geng, C Shah, ...
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
2142020
Towards long-term fairness in recommendation
Y Ge, S Liu, R Gao, Y Xian, Y Li, X Zhao, C Pei, F Sun, J Ge, W Ou, ...
Proceedings of the 14th ACM international conference on web search and data …, 2021
2012021
Understanding echo chambers in e-commerce recommender systems
Y Ge, S Zhao, H Zhou, C Pei, F Sun, W Ou, Y Zhang
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
1422020
Counterfactual explainable recommendation
J Tan, S Xu, Y Ge, Y Li, X Chen, Y Zhang
Proceedings of the 30th ACM International Conference on Information …, 2021
1292021
Towards personalized fairness based on causal notion
Y Li, H Chen, S Xu, Y Ge, Y Zhang
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
1232021
CAFE: Coarse-to-fine neural symbolic reasoning for explainable recommendation
Y Xian, Z Fu, H Zhao, Y Ge, X Chen, Q Huang, S Geng, Z Qin, G De Melo, ...
Proceedings of the 29th ACM International Conference on Information …, 2020
912020
Openagi: When llm meets domain experts
Y Ge, W Hua, K Mei, J Tan, S Xu, Z Li, Y Zhang
Advances in Neural Information Processing Systems 36, 2024
892024
Learning and evaluating graph neural network explanations based on counterfactual and factual reasoning
J Tan, S Geng, Z Fu, Y Ge, S Xu, Y Li, Y Zhang
Proceedings of the ACM Web Conference 2022, 1018-1027, 2022
872022
Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning
Y Ge, X Zhao, L Yu, S Paul, D Hu, CC Hsieh, Y Zhang
arXiv preprint arXiv:2201.00140, 2022
672022
Fairness in recommendation: A survey
Y Li, H Chen, S Xu, Y Ge, J Tan, S Liu, Y Zhang
arXiv preprint arXiv:2205.13619, 2022
662022
Path language modeling over knowledge graphsfor explainable recommendation
S Geng, Z Fu, J Tan, Y Ge, G De Melo, Y Zhang
Proceedings of the ACM Web Conference 2022, 946-955, 2022
612022
Explainable fairness in recommendation
Y Ge, J Tan, Y Zhu, Y Xia, J Luo, S Liu, Z Fu, S Geng, Z Li, Y Zhang
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
522022
Tutorial on fairness of machine learning in recommender systems
Y Li, Y Ge, Y Zhang
Proceedings of the 44th international ACM SIGIR conference on research and …, 2021
512021
sharedcharging: Data-driven shared charging for large-scale heterogeneous electric vehicle fleets
G Wang, W Li, J Zhang, Y Ge, Z Fu, F Zhang, Y Wang, D Zhang
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019
512019
How to index item ids for recommendation foundation models
W Hua, S Xu, Y Ge, Y Zhang
Proceedings of the Annual International ACM SIGIR Conference on Research and …, 2023
482023
Causal collaborative filtering
S Xu, Y Ge, Y Li, Z Fu, X Chen, Y Zhang
Proceedings of the 2023 ACM SIGIR International Conference on Theory of …, 2023
472023
A survey on trustworthy recommender systems
Y Ge, S Liu, Z Fu, J Tan, Z Li, S Xu, Y Li, Y Xian, Y Zhang
ACM Transactions on Recommender Systems, 2022
472022
Efficient non-sampling knowledge graph embedding
Z Li, J Ji, Z Fu, Y Ge, S Xu, C Chen, Y Zhang
Proceedings of the Web Conference 2021, 1727-1736, 2021
362021
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Articles 1–20