Publications

(2025). Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning. The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS'25).
(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).
(2024). StockCL: Selective Contrastive Learning for Stock Trend Forecasting via Learnable Concepts. Database Systems for Advanced Applications: 29th International Conference (DASFAA'24).
(2024). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators. The Twelfth International Conference on Learning Representations (ICLR'24).
(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).
(2023). RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction. ACM Transactions on Information System (TOIS).
(2023). Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey.
(2022). Mixed Information Flow for Cross-Domain Sequential Recommendations. ACM Transactions on Knowledge Discovery from Data (TKDD).