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cs.LG2026
ROAR: Retrieval Opportunity-Aware Refinement for Zero-Shot Time Series Forecasting
Jinjin Chi, Lei Feng, Lulu Zhang +7
Retrieval augmentation provides time series forecasters with historical continuations, yet even candidates that outperform the base forecast may fail to improve the final predictio…
cs.LG2025
Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering
Yiming Niu, Jinliang Deng, Lulu Zhang +2
Accurate and efficient multivariate time series (MTS) forecasting is essential for applications such as traffic management and weather prediction, which depend on capturing long-ra…
cs.LG2025
Understanding and Mitigating the High Computational Cost in Path Data Diffusion
Dingyuan Shi, Lulu Zhang, Yongxin Tong +1
Advancements in mobility services, navigation systems, and smart transportation technologies have made it possible to collect large amounts of path data. Modeling the distribution…