Do we really need graph neural networks for traffic forecasting? X Liu, Y Liang, C Huang, H Hu, Y Cao, B Hooi, R Zimmermann arXiv preprint arXiv:2301.12603, 2023 | 15 | 2023 |
Adaptive multi-modalities fusion in sequential recommendation systems H Hu, W Guo, Y Liu, MY Kan Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 7 | 2023 |
PM K-LightGCN: Optimizing for Accuracy and Popularity Match in Course Recommendation. Y Ran, H Hu, MY Kan Proceedings of the 16th ACM Conference on Recommender Systems, MORS Workshop, 2022 | 7 | 2022 |
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation J Wu, Q Liu, H Hu, W Fan, S Liu, Q Li, XM Wu, K Tang arXiv preprint arXiv:2310.09874, 2023 | 4 | 2023 |
Khanq: A dataset for generating deep questions in education H Gong, L Pan, H Hu Proceedings of the 29th International Conference on Computational …, 2022 | 4 | 2022 |
Modeling and Leveraging Prerequisite Context in Recommendation H Hu, L Pan, Y Ran, MY Kan Proceedings of the 16th ACM Conference on Recommender Systems, Context-Aware …, 2022 | 3 | 2022 |
Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision H Hu, Q Liu, C Li, MY Kan Proceedings of the 46th European Conference on Information Retrieval, 2024 | 2 | 2024 |
A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems C Li, H Hu, Y Zhang, MY Kan, H Li | 2 | 2023 |
Discrete Semantic Tokenization for Deep CTR Prediction Q Liu, H Hu, J Wu, J Zhu, MY Kan, XM Wu Proceedings of the ACM Web Conference 2024, 2024 | 1 | 2024 |
Automatic Feature Fairness in Recommendation via Adversaries H Hu, Y Cao, Z He, S Tan, MY Kan Proceedings of the International ACM SIGIR Conference on Information …, 2023 | 1 | 2023 |
User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation H Hu, W Guo, X Liu, Y Liu, R Tang, R Zhang, MY Kan WSDM 2024, 2024 | | 2024 |