| A general knowledge distillation framework for counterfactual recommendation via uniform data D Liu, P Cheng, Z Dong, X He, W Pan, Z Ming Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 203 | 2020 |
| 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 | 94 | 2021 |
| Large language models for generative recommendation: A survey and visionary discussions L Li, Y Zhang, D Liu, L Chen Proceedings of the 2024 Joint International Conference on Computational …, 2023 | 90 | 2023 |
| FLEN: Leveraging field for scalable CTR prediction W Chen, L Zhan, Y Ci, M Yang, C Lin, D Liu Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD …, 2019 | 27 | 2019 |
| Spiral of silence in recommender systems D Liu, C Lin, Z Zhang, Y Xiao, H Tong Proceedings of the 12th ACM International Conference on Web Search and Data …, 2019 | 25 | 2019 |
| Optimizing feature set for click-through rate prediction F Lyu, X Tang, D Liu, L Chen, X He, X Liu Proceedings of the ACM Web Conference 2023, 3386-3395, 2023 | 24 | 2023 |
| KDCRec: Knowledge distillation for counterfactual recommendation via uniform data D Liu, P Cheng, Z Lin, J Luo, Z Dong, X He, W Pan, Z Ming IEEE Transactions on Knowledge and Data Engineering 35 (8), 8143-8156, 2022 | 20 | 2022 |
| Automatically inspecting thousands of static bug warnings with large language model: How far are we? C Wen, Y Cai, B Zhang, J Su, Z Xu, D Liu, S Qin, Z Ming, C Tian ACM Transactions on Knowledge Discovery from Data 18 (7), 168:1-168:34, 2024 | 15 | 2024 |
| Debiased representation learning in recommendation via information bottleneck D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming ACM Transactions on Recommender Systems 1 (1), 1-27, 2023 | 15 | 2023 |
| Augmenting legal judgment prediction with contrastive case relations D Liu, W Du, L Li, W Pan, Z Ming Proceedings of the 29th International Conference on Computational …, 2022 | 14 | 2022 |
| Explicit feature interaction-aware uplift network for online marketing D Liu, X Tang, H Gao, F Lyu, X He Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 13 | 2023 |
| User-event graph embedding learning for context-aware recommendation D Liu, M He, J Luo, J Lin, M Wang, X Zhang, W Pan, Z Ming Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 13 | 2022 |
| Transfer learning for collaborative recommendation with biased and unbiased data Z Lin, D Liu, W Pan, Q Yang, Z Ming Artificial Intelligence 324, 103992, 2023 | 12 | 2023 |
| Spiral of silence and its application in recommender systems C Lin, D Liu, H Tong, Y Xiao IEEE Transactions on Knowledge and Data Engineering 34 (6), 2934-2947, 2020 | 12 | 2020 |
| Transfer learning in collaborative recommendation for bias reduction Z Lin, D Liu, W Pan, Z Ming Proceedings of the 15th ACM Conference on Recommender Systems, 736-740, 2021 | 11 | 2021 |
| Recommendation with social roles D Liu, J Huang, C Lin IEEE Access 6, 36420-36427, 2018 | 10 | 2018 |
| MultiFS: Automated multi-scenario feature selection in deep recommender systems D Liu, C Yang, X Tang, Y Wang, F Lyu, W Luo, X He, Z Ming, X Zhao Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 7 | 2024 |
| DIWIFT: Discovering instance-wise influential features for tabular data D Liu, P Cheng, H Zhu, X Tang, Y Chen, X Wang, W Pan, Z Ming, X He Proceedings of the ACM Web Conference 2023, 1673-1682, 2023 | 7 | 2023 |
| Bounding system-induced biases in recommender systems with a randomized dataset D Liu, P Cheng, Z Lin, X Zhang, Z Dong, R Zhang, X He, W Pan, Z Ming ACM Transactions on Information Systems 41 (4), 1-26, 2023 | 7 | 2023 |
| Unbiased recommendation model based on improved propensity score estimation J LUO, D LIU, W PAN, Z MING Journal of Computer Applications 41 (12), 3508-3514, 2021 | 7 | 2021 |
Xiuqiang HeHKUST, TencentEmail verificata su tencent.com
