Pre-print papers and published papers in journals and conferences are listed here. Corresponding authors are marked with *, and equal contributions are noted with underlines.
More information can be found in my Google Scholar page.

Pre-prints

1. Zhenqian Shen, Yongqi Zhang, Lanning Wei, Huan Zhao and Quanming Yao*. Automated Machine Learning: A Survey From Principles to Practices.

Journals

1. Mingze Gong, Yongqi Zhang*, Jia Li and Lei Chen. Dynamic Spatial-Temporal Model for Carbon Emission Forecasting. Journal of Cleaner Production (IF 11.1) 2024. code
2. Xiang Li, Yongqi Zhang, Lei Chen, Jia Li and Xiaowen Chu*. A Decomposition-Ensemble-Integration Framework for Carbon Price Forecasting. Expert Systems With Applications (IF 13.8) 2024.
3. Yongqi Zhang, Quanming Yao*, LinYue, XianWu, Ziheng Zhang, Zhenxi Lin and Yefeng Zheng. EmerGNN: Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network. Nature Computational Science 2023. code
4. Yongqi Zhang, Quanming Yao* and James T. Kwok. Bilinear Scoring Function Search for Knowledge Graph Learning. IEEE TPAMI 2023. code
5. Yongqi Zhang, Quanming Yao* and Lei Chen. Simple and Automated Negative Sampling for Knowledge Graph Embedding. VLDB-Journal 2021. code

Conferences

1. Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao and Bo Han*. Less is more: One-shot-subgraph Link Prediction on Large-Scale Knowledge Graph. ICLR 2024. code
2. Haiquan Qiu, Yongqi Zhang, Yong Li and Quanming Yao*. Understanding Expressivity of GNN in Rule Learning. ICLR 2024. code
3. Yuhong He, Yongqi Zhang, Shuzhi He and Jun Wan*. BP4ER: Bootstrap Prompting for Explicit Reasoning in Medical Dialogue Generation. LREC-COLING 2024.
4. Guangyi Liu, Quanming Yao, Yongqi Zhang* and Lei Chen. Knowledge-Enhanced Recommendation with User-Centric Subgraph Network. ICDE 2024. code
5. Xinyi Zhu, Yongqi Zhang*, Lei Chen and Kai Chen. Triple-d: Denoising Distant Supervision for High-quality Data Creation. ICDE 2024. code
6. Fuda Ye, Shuangyin Li*, Yongqi Zhang and Lei Chen. R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation. Findings of EMNLP 2024.
7. Fangqi Zhu, Yongqi Zhang*, Lei Chen, Bing Qin and Ruifeng Xu*. Learning to Describe for Predicting Zero-shot Drug-Drug Interactions. EMNLP 2023. code
8. Ling Yue, Yongqi Zhang, Quanming Yao*, XianWu, Ziheng Zhang, Zhenxi Lin and Yefeng Zheng. Relation-aware Ensemble Learning for Knowledge Graph Embedding. EMNLP 2023. code
9. Yongqi Zhang, Zhanke Zhou, Quanming Yao*, Xiaowen Chu and Bo Han. Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. KDD 2023. code
10. Hansi Yang, Yongqi Zhang, Quanming Yao and James T. Kwok. Positive-Unlabeled Node Classification with Structure-aware Graph Learning. CIKM 2023.
11. Yongqi Zhang, Hui Zhang, Quanming Yao and Jun Wan*. Combining Self-Supervised and Supervised Learning with Noisy Labels. ICIP 2023.
12. Yongqi Zhang and Quanming Yao*. Knowledge Graph Reasoning with Relational Directed Graph. WebConf 2022. code
13. Yongqi Zhang, Zhanke Zhou, Yong Li and Quanming Yao*. KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning. ACL 2022. code
14. Shimin Di, Quanming Yao*, Yongqi Zhang and Lei Chen. Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding. ICDE 2021. code
15. Yongqi Zhang, Quanming Yao* and Lei Chen Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding. NeurIPS 2020. code
16. Yongqi Zhang, Quanming Yao*, Wenyuan Dai and Lei Chen. AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. ICDE 2020. code
17. Yongqi Zhang, Quanming Yao*, Yingxia Shao and Lei Chen. NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. ICDE 2019. code