| Heterogeneous similarity graph neural network on electronic health records Z Liu, X Li, H Peng, L He, SY Philip 2020 IEEE international conference on big data (big data), 1196-1205, 2020 | 91 | 2020 |
| Dynamic Graph Collaborative Filtering X Li, M Zhang, S Wu, Z Liu, L Wang, SY Philip 2020 IEEE international conference on data mining (ICDM), 322-331, 2020 | 81 | 2020 |
| 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 | 67 | 2020 |
| Blood pressure prediction via recurrent models with contextual layer X Li, S Wu, L Wang Proceedings of the 26th International Conference on World Wide Web, 685-693, 2017 | 61 | 2017 |
| Relation labeling in product knowledge graphs with large language models for e-commerce J Chen*, L Ma*, X Li*, J Xu, JHD Cho, K Nag, E Korpeoglu, S Kumar, ... International Journal of Machine Learning and Cybernetics, 1-19, 2024 | 33* | 2024 |
| Llm-ensemble: Optimal large language model ensemble method for e-commerce product attribute value extraction C Fang*, X Li*, Z Fan, J Xu, K Nag, E Korpeoglu, S Kumar, K Achan Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | 26* | 2024 |
| Pre-training recommender systems via reinforced attentive multi-relational graph neural network X Li, Z Liu, S Guo, Z Liu, H Peng, SY Philip, K Achan 2021 IEEE International Conference on Big Data (Big Data), 457-468, 2021 | 22 | 2021 |
| Medical triage chatbot diagnosis improvement via multi-relational hyperbolic graph neural network Z Liu*, X Li*, Z You, T Yang, W Fan, P Yu Proceedings of the 44th International ACM SIGIR conference on research and …, 2021 | 20 | 2021 |
| Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation X Li, Y Liu, Z Liu, PS Yu 2022 IEEE International Conference on Big Data (Big Data), 626-635, 2023 | 16 | 2023 |
| Mitigating health disparities in ehr via deconfounder Z Liu, X Li, P Yu Proceedings of the 13th ACM International Conference on Bioinformatics …, 2022 | 10 | 2022 |
| Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders X Li, Z Liu, L Ma, K Nag, S Guo, P Yu, K Achan 2022 IEEE International Conference on Big Data (Big Data), 616-625, 2022 | 8* | 2022 |
| Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation X Liu, L Yang, Z Liu, X Li, M Yang, C Wang, SY Philip 2023 IEEE International Conference on Big Data (BigData), 393-402, 2023 | 7 | 2023 |
| Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding Z Fan*, X Li*, K Nag, C Fang, T Biswas, J Xu, K Achan Companion Proceedings of the ACM on Web Conference 2024, 1530-1537, 2024 | 6* | 2024 |
| A counterfactual fair model for longitudinal electronic health records via deconfounder Z Liu, X Li, SY Philip 2023 IEEE International Conference on Data Mining (ICDM), 1175-1180, 2023 | 2 | 2023 |
| 3rd international workshop on industrial recommendation systems (irs) L Ma, X Li, K Ahmadi, J Xu, PS Yu, G Karypis Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 1 | 2024 |
| Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations L Ma*, X Li*, Z Fan*, J Xu, J Cho, P Kanumala, K Nag, S Kumar, K Achan arXiv preprint arXiv:2410.12228, 2024 | 1 | 2024 |
| Multi-task Recommendation in Marketplace via Knowledge Attentive Graph Convolutional Network with Adaptive Contrastive Learning X Li, Z Fan, L Ma, K Nag, K Achan 2024 IEEE International Conference on Big Data (BigData), 2162-2169, 2024 | | 2024 |
| Improving Sequential Recommender Systems with Online and In-store User Behavior L Ma, A Padmanabhan, A Ganesh, S Tang, J Chen, X Li, L Morishetti, ... 2024 IEEE International Conference on Big Data (BigData), 3544-3549, 2024 | | 2024 |
Philip S. YuProfessor of Computer Science, University of Illinons at ChicagoDirección de correo verificada de cs.uic.edu