| Cl4ctr: A contrastive learning framework for ctr prediction F Wang, Y Wang, D Li, H Gu, T Lu, P Zhang, N Gu Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 29 | 2023 |
| Enhancing CTR prediction with context-aware feature representation learning F Wang, Y Wang, D Li, H Gu, T Lu, P Zhang, N Gu Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 28 | 2022 |
| Improving the expressiveness of k-hop message-passing gnns by injecting contextualized substructure information T Yao, Y Wang, K Zhang, S Liang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 6 | 2023 |
| Heterogeneous graph contrastive learning with metapath-based augmentations X Chen, Y Wang, J Fang, Z Meng, S Liang IEEE Transactions on Emerging Topics in Computational Intelligence, 2023 | 4 | 2023 |
| Enhancing conversational recommendation systems with representation fusion Y Wang, X Chen, J Fang, Z Meng, S Liang ACM Transactions on the Web 17 (1), 1-34, 2023 | 4 | 2023 |
| A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction F Wang, Y Wang, H Gu, D Li, T Lu, P Zhang, L Shang, N Gu arXiv preprint arXiv:2311.04625, 2023 | | 2023 |
| GOING BEYOND 1-WL EXPRESSIVE POWER WITH 1-LAYER GRAPH NEURAL NETWORKS T Yao, Y Wang, S Liang | | |
