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| Mitigating confounding bias in recommendation via information bottleneck D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming Proceedings of the 15th ACM conference on Recommender systems, 351-360, 2021 | 96 | 2021 |
| Improving ad click prediction by considering non-displayed events B Yuan, JY Hsia, MY Yang, H Zhu, CY Chang, Z Dong, CJ Lin Proceedings of the 28th ACM International Conference on Information and …, 2019 | 95 | 2019 |
| Deepfm: An end-to-end wide & deep learning framework for CTR prediction H Guo, R Tang, Y Ye, Z Li, X He, Z Dong arXiv preprint arXiv:1804.04950, 2018 | 88 | 2018 |
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| A survey on the memory mechanism of large language model based agents Z Zhang, X Bo, C Ma, R Li, X Chen, Q Dai, J Zhu, Z Dong, JR Wen arXiv preprint arXiv:2404.13501, 2024 | 76 | 2024 |
| FinalMLP: an enhanced two-stream MLP model for CTR prediction K Mao, J Zhu, L Su, G Cai, Y Li, Z Dong Proceedings of the AAAI conference on artificial intelligence 37 (4), 4552-4560, 2023 | 76 | 2023 |
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| On the opportunity of causal learning in recommendation systems: Foundation, estimation, prediction and challenges P Wu, H Li, Y Deng, W Hu, Q Dai, Z Dong, J Sun, R Zhang, XH Zhou arXiv preprint arXiv:2201.06716, 2022 | 69 | 2022 |
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| Explainable legal case matching via inverse optimal transport-based rationale extraction W Yu, Z Sun, J Xu, Z Dong, X Chen, H Xu, JR Wen Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 50 | 2022 |
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Ji-Rong WenRenmin University of ChinaПотвърден имейл адрес: ruc.edu.cn
