| Enhancing graph neural network-based fraud detectors against camouflaged fraudsters Y Dou, Z Liu, L Sun, Y Deng, H Peng, PS Yu Proceedings of the 29th ACM international conference on information …, 2020 | 370 | 2020 |
| Alleviating the inconsistency problem of applying graph neural network to fraud detection Z Liu, Y Dou, PS Yu, Y Deng, H Peng Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 218 | 2020 |
| Intent contrastive learning for sequential recommendation Y Chen, Z Liu, J Li, J McAuley, C Xiong Proceedings of the ACM Web Conference 2022, 2172-2182, 2022 | 180 | 2022 |
| Continuous-time sequential recommendation with temporal graph collaborative transformer Z Liu*, Z Fan*, J Zhang, Y Xiong, L Zheng, PS Yu Proceedings of the 30th ACM International Conference on Information …, 2021 | 153 | 2021 |
| Contrastive self-supervised sequential recommendation with robust augmentation Z Liu, Y Chen, J Li, PS Yu, J McAuley, C Xiong arXiv preprint arXiv:2108.06479, 2021 | 138 | 2021 |
| Augmenting sequential recommendation with pseudo-prior items via reversely pre-training transformer Z Liu, Z Fan, Y Wang, PS Yu Proceedings of the 44th international ACM SIGIR conference on Research and …, 2021 | 127 | 2021 |
| Consisrec: Enhancing gnn for social recommendation via consistent neighbor aggregation L Yang, Z Liu, Y Dou, J Ma, PS Yu Proceedings of the 44th international ACM SIGIR conference on Research and …, 2021 | 122 | 2021 |
| Federated social recommendation with graph neural network Z Liu, L Yang, Z Fan, H Peng, PS Yu ACM Transactions on Intelligent Systems and Technology (TIST) 13 (4), 1-24, 2022 | 119 | 2022 |
| Sequential recommendation via stochastic self-attention Z Fan, Z Liu, Y Wang, A Wang, Z Nazari, L Zheng, H Peng, PS Yu Proceedings of the ACM web conference 2022, 2036-2047, 2022 | 105 | 2022 |
| Basconv: Aggregating heterogeneous interactions for basket recommendation with graph convolutional neural network Z Liu, M Wan, S Guo, K Achan, PS Yu Proceedings of the 2020 SIAM International Conference on Data Mining, 64-72, 2020 | 76 | 2020 |
| Few-shot intent detection via contrastive pre-training and fine-tuning J Zhang, T Bui, S Yoon, X Chen, Z Liu, C Xia, QH Tran, W Chang, P Yu arXiv preprint arXiv:2109.06349, 2021 | 69 | 2021 |
| Basket recommendation with multi-intent translation graph neural network Z Liu, X Li, Z Fan, S Guo, K Achan, SY Philip 2020 IEEE International Conference on Big Data (Big Data), 728-737, 2020 | 57 | 2020 |
| Dskreg: Differentiable sampling on knowledge graph for recommendation with relational gnn Y Wang, Z Liu, Z Fan, L Sun, PS Yu Proceedings of the 30th ACM International Conference on Information …, 2021 | 55 | 2021 |
| Bolaa: Benchmarking and orchestrating llm-augmented autonomous agents Z Liu, W Yao, J Zhang, L Xue, S Heinecke, R Murthy, Y Feng, Z Chen, ... arXiv preprint arXiv:2308.05960, 2023 | 46 | 2023 |
| Pre-training graph neural network for cross domain recommendation C Wang, Y Liang, Z Liu, T Zhang, SY Philip 2021 IEEE Third International Conference on Cognitive Machine Intelligence …, 2021 | 42 | 2021 |
| Large-scale personalized video game recommendation via social-aware contextualized graph neural network L Yang, Z Liu, Y Wang, C Wang, Z Fan, PS Yu Proceedings of the ACM Web Conference 2022, 3376-3386, 2022 | 40 | 2022 |
| Modeling sequences as distributions with uncertainty for sequential recommendation Z Fan, Z Liu, S Wang, L Zheng, PS Yu Proceedings of the 30th ACM international conference on information …, 2021 | 37 | 2021 |
| Retroformer: Retrospective large language agents with policy gradient optimization W Yao, S Heinecke, JC Niebles, Z Liu, Y Feng, L Xue, R Murthy, Z Chen, ... arXiv preprint arXiv:2308.02151, 2023 | 34 | 2023 |
| Contrastvae: Contrastive variational autoencoder for sequential recommendation Y Wang, H Zhang, Z Liu, L Yang, PS Yu Proceedings of the 31st ACM International Conference on Information …, 2022 | 33 | 2022 |
| Are pretrained transformers robust in intent classification? a missing ingredient in evaluation of out-of-scope intent detection J Zhang, K Hashimoto, Y Wan, Z Liu, Y Liu, C Xiong, PS Yu arXiv preprint arXiv:2106.04564, 2021 | 30 | 2021 |
Philip S. YuProfessor of Computer Science, University of Illinons at Chicago在 cs.uic.edu 的电子邮件经过验证
