| Nais: Neural attentive item similarity model for recommendation X He, Z He, J Song, Z Liu, YG Jiang, TS Chua TKDE'18, 2018 | 540 | 2018 |
| Adversarial personalized ranking for recommendation X He, Z He, X Du, TS Chua SIGIR'18, 2018 | 418 | 2018 |
| Meal: Multi-model ensemble via adversarial learning Z Shen*, Z He*, X Xue AAAI'19, 2019 | 150 | 2019 |
| Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders Y Hou, Z He, J McAuley, WX Zhao WWW'23, 2023 | 75 | 2023 |
| Large Language Models as Zero-Shot Conversational Recommenders Z He*, Z Xie*, R Jha, H Steck, D Liang, Y Feng, BP Majumder, N Kallus, ... CIKM'23, 2023 | 72 | 2023 |
| Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction Z Yue*, Z He*, H Zeng, J McAuley RecSys'21, 2021 | 65 | 2021 |
| Locker: Locally Constrained Self-Attentive Sequential Recommendation Z He, H Zhao, Z Lin, Z Wang, A Kale, J McAuley CIKM'21, 2021 | 51 | 2021 |
| Weakly supervised attention for hashtag recommendation using graph data A Javari, Z He, Z Huang, R Jeetu, K Chen-Chuan Chang WWW'20, 2020 | 29 | 2020 |
| Personalized Showcases: Generating Multi-Modal Explanations for Recommendations A Yan*, Z He*, J Li*, T Zhang, J McAuley SIGIR'23, 2023 | 23 | 2023 |
| Bundle MCR: Towards Conversational Bundle Recommendation Z He, H Zhao, T Yu, S Kim, F Du, J McAuley RecSys'22, 2022 | 23 | 2022 |
| Leashing the Inner Demons: Self-Detoxification for Language Models C Xu, Z He, Z He, J McAuley AAAI'22, 2022 | 17 | 2022 |
| Bridging language and items for retrieval and recommendation Y Hou, J Li, Z He, A Yan, X Chen, J McAuley arXiv preprint arXiv:2403.03952, 2024 | 13 | 2024 |
| Linear recurrent units for sequential recommendation Z Yue, Y Wang, Z He, H Zeng, J McAuley, D Wang Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 12 | 2024 |
| Generative Flow Network for Listwise Recommendation S Liu, Q Cai, Z He, B Sun, J McAuley, D Zheng, P Jiang, K Gai KDD'23, 2023 | 11 | 2023 |
| Query-Aware Sequential Recommendation Z He, H Zhao, Z Wang, Z Lin, A Kale, J McAuley CIKM'22, 2022 | 11 | 2022 |
| Adversarial-based knowledge distillation for multi-model ensemble and noisy data refinement Z Shen, Z He, W Cui, J Yu, Y Zheng, C Zhu, M Savvides arXiv preprint arXiv:1908.08520, 2019 | 7 | 2019 |
| Ucepic: Unifying aspect planning and lexical constraints for generating explanations in recommendation J Li, Z He, J Shang, J McAuley Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 6 | 2023 |
| A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys) Y Deldjoo, Z He, J McAuley, A Korikov, S Sanner, A Ramisa, R Vidal, ... arXiv preprint arXiv:2404.00579, 2024 | 5 | 2024 |
| Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders. CoRR abs/2210.12316 (2022) Y Hou, Z He, JJ McAuley, WX Zhao | 5 | 2022 |
| Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation S Yoon, Z He, JM Echterhoff, J McAuley arXiv preprint arXiv:2403.09738, 2024 | 4 | 2024 |
