Hao Zhang

According to our database, Hao Zhang authored at least 14 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Cross-Domain Pre-training with Language Models for Transferable Time Series Representations.

Mingyue Cheng, Xiaoyu Tao, Qi Liu, Hao Zhang, Yiheng Chen, Defu Lian

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

2024

Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendation.

Yucong Luo, Qitao Qin, Hao Zhang, Mingyue Cheng, Ruiran Yan, Kefan Wang, Jie Ouyang

CoRR, 2024

Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation.

Li Li, Mingyue Cheng, Zhiding Liu, Hao Zhang, Qi Liu, Enhong Chen

CoRR, 2024

Learning Transferable Time Series Classifier with Cross-Domain Pre-training from Language Model.

Mingyue Cheng, Xiaoyu Tao, Qi Liu, Hao Zhang, Yiheng Chen, Chenyi Lei

CoRR, 2024

Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform.

Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Optimizing Code Retrieval: High-Quality and Scalable Dataset Annotation through Large Language Models.

Rui Li, Qi Liu, Liyang He, Zheng Zhang, Hao Zhang, Shengyu Ye, Junyu Lu, Zhenya Huang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Learning Recommender Systems with Soft Target: A Decoupled Perspective.

Hao Zhang, Mingyue Cheng, Qi Liu, Yucong Luo, Rui Li, Enhong Chen

Proceedings of the Database Systems for Advanced Applications, 2024

Unlocking the Potential of Large Language Models for Explainable Recommendations.

Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Enhong Chen

Proceedings of the Database Systems for Advanced Applications, 2024

Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling.

Junzhe Jiang, Shang Qu, Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Kai Zhang, Rui Li, Jiatong Li, Min Gao

Proceedings of the Database Systems for Advanced Applications, 2024

Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness.

Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li

Proceedings of the Database Systems for Advanced Applications, 2024

Learning the Dynamics in Sequential Recommendation by Exploiting Real-time Information.

Rujiao Zhang, Hao Zhang, Yucong Luo, Zhiding Liu, Mingyue Cheng, Qi Liu, Enhong Chen

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Unlocking the Potential of Large Language Models for Explainable Recommendations.

Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Qi Liu, Enhong Chen

CoRR, 2023

Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems.

Hao Zhang, Mingyue Cheng, Qi Liu, Zhiding Liu, Enhong Chen

CoRR, 2023

TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders.

Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Enhong Chen

CoRR, 2023