| Knowledge Editing for Large Language Models: A Survey S Wang, Y Zhu, H Liu, Z Zheng, C Chen, J Li ACM Computing Survey (CSUR), 2023 | 97 | 2023 |
| Collaborative Large Language Model for Recommender Systems Y Zhu, L Wu, Q Guo, L Hong, J Li ACM Web Conference (WWW), 2024 | 51 | 2024 |
| A multimodal variational encoder-decoder framework for micro-video popularity prediction J Xie*, Y Zhu*, Z Zhang, J Peng, J Yi, Y Hu, H Liu, Z Chen ACM Web Conference (WWW), 2020 | 48* | 2020 |
| Cross-modal variational auto-encoder for content-based micro-video background music recommendation J Yi, Y Zhu, J Xie, Z Chen IEEE Transactions on Multimedia (TMM), 2021 | 45 | 2021 |
| Usable XAI: 10 strategies towards exploiting explainability in the LLM era X Wu, H Zhao, Y Zhu, Y Shi, F Yang, T Liu, X Zhai, W Yao, J Li, M Du, ... arXiv preprint arXiv:2403.08946, 2024 | 33 | 2024 |
| Micro-video popularity prediction via multimodal variational information bottleneck J Xie, Y Zhu, Z Chen IEEE Transactions on Multimedia (TMM), 2021 | 25 | 2021 |
| Mutually-regularized dual collaborative variational auto-encoder for recommender systems Y Zhu, Z Chen ACM Web Conference (WWW), 2022 | 24 | 2022 |
| Multimodal deep denoise framework for affective video content analysis Y Zhu, Z Chen, F Wu ACM International Conference on Multimedia (ACM MM), 2019 | 19 | 2019 |
| Causal Inference and Recommendations Y Zhu, J Ma, J Li Machine Learning for Causal Inference, Springer, 2023 | 17* | 2023 |
| Variational bandwidth auto-encoder for hybrid recommender systems Y Zhu, Z Chen IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 | 17* | 2022 |
| Deep causal reasoning for recommendations Y Zhu, J Yi, J Xie, Z Chen ACM Transactions on Intelligent Systems and Technology (TIST), 2022 | 13 | 2022 |
| Knowledge Graph-Enhanced Large Language Models via Path Selection H Liu, S Wang, Y Zhu, Y Dong, J Li Annual Meeting of the Association for Computational Linguistics (ACL), 2024 | 11 | 2024 |
| Path-Specific Counterfactual Fairness for Recommender Systems Y Zhu, J Ma, L Wu, Q Guo, L Hong, J Li ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023 | 9 | 2023 |
| Affective video content analysis via multimodal deep quality embedding network Y Zhu, Z Chen, F Wu IEEE Transactions on Affective Computing (TAFFC), 2020 | 7 | 2020 |
| Automatic changes detection between outdated building maps and new VHR images based on pre-trained fully convolutional feature maps Y Zhang, Y Zhu, H Li, S Chen, J Peng, L Zhao Sensors 20 (19), 5538, 2020 | 3 | 2020 |
| Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations L Guo, Y Zhu, M Gao, Y Tao, J Yu, C Chen ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 | 2 | 2024 |
| Causal Inference with Latent Variables: Recent Advances and Future Prospectives Y Zhu, Y He, J Ma, M Hu, S Li, J Li ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 | 2 | 2024 |
| Deep deconfounded content-based tag recommendation for UGC with causal intervention X Ren*, Y Zhu*, J Yi, Z Chen arXiv preprint arXiv:2205.14380, 2022 | 2 | 2022 |
| Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems Y Zhu, C Wan, H Steck, D Liang, Y Feng, N Kallus, J Li ACM Web Conference (WWW), 2025 | | 2025 |
| Collaborative Diffusion Model for Recommender Systems G Lee, Y Zhu, H Yu, Y Zhou, J Li ACM Web Conference (WWW), 2025 | | 2025 |
Jundong LiAssistant Professor, University of VirginiaVerified email at virginia.edu
