Publications

Lifan Zhao, Yanyan Shen, Zhaoyang Liu, Xue Wang, Jiaji Deng (2025). Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning.

Lifan Zhao, Yanyan Shen (2025). Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'25).

Zexi Zhang, Lifan Zhao, Yanyan Shen, Bin Yao (2024). StockCL: Selective Contrastive Learning for Stock Trend Forecasting via Learnable Concepts. Database Systems for Advanced Applications: 29th International Conference (DASFAA'24).

Lifan Zhao, Yanyan Shen (2024). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators. The Twelfth International Conference on Learning Representations (ICLR'24).

Lifan Zhao, Shuming Kong, Yanyan Shen (2023). DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'23).

Yanyan Shen, Lifan Zhao, Weiyu Cheng, Zibin Zhang, Wenwen Zhou, Lin Kangyi (2023). RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction. ACM Transactions on Information System (TOIS).

Liping Wang, Jiawei Li, Lifan Zhao, Zhizhuo Kou, Xiaohan Wang, Xinyi Zhu, Hao Wang, Yanyan Shen, Lei Chen (2023). Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey.

Muyang Ma, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Lifan Zhao, Peiyu Liu, Jun Ma, Maarten De Rijke (2022). Mixed Information Flow for Cross-Domain Sequential Recommendations. ACM Transactions on Knowledge Discovery from Data (TKDD).