| ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models Q Liu, N Chen, T Sakai, XM Wu WSDM'24, 2023 | 38* | 2023 |
| Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation Q Liu, J Zhu, Q Dai, XM Wu COLING'22, 2022 | 22 | 2022 |
| Weak supervision enhanced generative network for question generation Y Wang, J Zheng, Q Liu, Z Zhao, J Xiao, Y Zhuang IJCAI'19, 2019 | 8 | 2019 |
| 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 |
| FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation Q Liu, J Zhu, J Wu, T Wu, Z Dong, XM Wu WWW'23, 2023 | 4 | 2023 |
| Dataset Condensation for Recommendation J Wu, W Fan, S Liu, Q Liu, R He, Q Li, K Tang arXiv preprint arXiv:2310.01038, 2023 | 3 | 2023 |
| Continual Graph Convolutional Network for Text Classification T Wu*, Q Liu*, Y Cao, Y Huang, XM Wu, J Ding AAAI'23, 2023 | 3 | 2023 |
| Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision H Hu, Q Liu, C Li, MY Kan ECIR'24, 2024 | 2 | 2024 |
| Discrete Semantic Tokenization for Deep CTR Prediction Q Liu, H Hu, J Wu, J Zhu, MY Kan, XM Wu WWW'24, 2024 | 1 | 2024 |
| Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling J Wu, W Fan, S Liu, Q Liu, Q Li, K Tang arXiv preprint arXiv:2309.12723, 2023 | 1 | 2023 |
| Benchmarking News Recommendation in the Era of Green AI Q Liu*, J Zhu*, Q Dai, XM Wu WWW'24, 2024 | | 2024 |
| Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey Q Liu*, J Zhu*, Y Yang, Q Dai, Z Du, XM Wu, Z Zhao, R Zhang, Z Dong arXiv preprint arXiv:2404.00621, 2024 | | 2024 |
| Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization Q Liu, L Fan*, J Xiao*, J Zhu, XM Wu WWW'24, 2023 | | 2023 |
| Making Multimodal Generation Easier: When Diffusion Models Meet LLMs X Zhao, B Liu*, Q Liu*, G Shi*, XM Wu arXiv preprint arXiv:2310.08949, 2023 | | 2023 |
| Only Encode Once: Making Content-based News Recommender Greener Q Liu, J Zhu, Q Dai, XM Wu arXiv preprint arXiv:2308.14155, 2023 | | 2023 |
| Legommenders: A Modular Framework for Recommender Systems Q Liu Online Resource (Github), 2023 | | 2023 |
Xiao-Ming WuAssociate Professor, The Hong Kong Polytechnic UniversityVerified email at polyu.edu.hk
