MultiMix: A Multi-Task Deep Learning Approach for Travel Mode Identification with Few GPS Data. - Xiaozhuang Song; Christos Markos; James J. Q. Yu (ITSC, 2020)

TSTNet: A Sequence to Sequence Transformer Network for Spatial-Temporal Traffic Prediction. - Xiaozhuang Song; Ying Wu; Chenhan Zhang (ICANN (1), 2021)

TINet: Multi-dimensional Traffic Data Imputation via Transformer Network. - Xiaozhuang Song; Yongchao Ye; James J. Q. Yu (ICANN (1), 2021)

Transfer Learning in Traffic Prediction with Graph Neural Networks. - Yunjie Huang; Xiaozhuang Song; Shiyao Zhang; James J. Q. Yu (ITSC, 2021)

Learn Travel Time Distribution with Graph Deep Learning and Generative Adversarial Network. - Xiaozhuang Song; Chenhan Zhang; James J. Q. Yu (ITSC, 2021)

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. - Kingsley Nweye; Zoltán Nagy 002; Sharada P. Mohanty; Dipam Chakraborty; Siva Sankaranarayanan; Tianzhen Hong; Sourav Dey; Gregor Henze; Ján Drgona; Fangquan Lin; Wei Jiang 027; Hanwei Zhang 002; et al. (NeurIPS (Competition and Demos), 2021)

Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel. - Chenhan Zhang; Qingpeng Zhang; Shui Yu 001; James J. Q. Yu; Xiaozhuang Song (IEEE Trans. Comput. Soc. Syst., 2021)

Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. - Xiaozhuang Song; Shun Zheng 001; Wei Cao 007; James J. Q. Yu; Jiang Bian 002 (NeurIPS, 2022)

Traffic Prediction With Missing Data: A Multi-Task Learning Approach. - Ao Wang; Yongchao Ye; Xiaozhuang Song; Shiyao Zhang; James J. Q. Yu (IEEE Trans. Intell. Transp. Syst., 2023)

Traffic Prediction With Transfer Learning: A Mutual Information-Based Approach. - Yunjie Huang; Xiaozhuang Song; Yuanshao Zhu; Shiyao Zhang; James J. Q. Yu (IEEE Trans. Intell. Transp. Syst., 2023)

Single Cell Gene Expression Prediction via Prototype-based Proximal Neural Factorization. - Xiaozhuang Song; Xu Liao; Hangting Ye; Yaoyao Xu; Wei Fan 010; Jin Liu; Tianshu Yu 001 (BIBM, 2024)

PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. - Hangting Ye; Wei Fan 010; Xiaozhuang Song; Shun Zheng 001; He Zhao 001; Dandan Guo; Yi Chang 001 (ICLR, 2024)

Boosting Protein Language Models with Negative Sample Mining. - Yaoyao Xu; Xinjian Zhao; Xiaozhuang Song; Benyou Wang; Tianshu Yu 001 (ECML/PKDD (10), 2024)

GT-TTE: Modeling Trajectories as Graphs for Travel Time Estimation. - Yunjie Huang; Xiaozhuang Song; Shiyao Zhang; Lei Li 003; James Jian Qiao Yu (IEEE Internet Things J., 2024)

Enhancing Generalizability in Molecular Conformation Generation with METRIZATION-Informed Geometric Diffusion Pretraining. - Xiaozhuang Song; Yuzhao Tu; Hangting Ye; Wei Fan 010; Qingquan Zhang; Xiaoxue Wang; Tianshu Yu 001 (AAAI, 2025)

ReKG-MCTS: Reinforcing LLM Reasoning on Knowledge Graphs via Training-Free Monte Carlo Tree Search. - Xiaozhuang Song; Shufei Zhang; Tianshu Yu 001 (ACL (Findings), 2025)

Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification. - Wei Fan 010; Jingru Fei; Dingyu Guo; Kun Yi 001; Xiaozhuang Song; Haolong Xiang; Hangting Ye; Min Li 007 (WWW, 2025)

Enhancing Molecular Conformer Generation via Fragment- Augmented Diffusion Pretraining. - Xiaozhuang Song; Yuzhao Tu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)

MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification. - Wei Fan 010; Jingru Fei; Dingyu Guo; Kun Yi 001; Xiaozhuang Song; Haolong Xiang; Hangting Ye; Min Li 007 (CoRR, 2025)