Sep 2026
TFB-2: benchmarking and automated ensemble for time series forecasting
Zhengyu Li, Xingjian Wu, Xiangfei Qiu et al.
· The VLDB journal · 0 citations
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BITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting
BITS, a standardized, reproducible, and extensible benchmark for advancing research on irregular time series forecasting, is proposed and it is found that method performance varies substantially across irregularity characteristics, with no single modeling strategy consistently dominating.
Kang-Jia Yan, Lin-Feng Wang, Tian Shen et al.
· 0 citations
WorldTS: World Modeling for Multimodal Covariate-aware Time Series Forecasting
This work proposes WorldTS, a world-modeling based forecasting framework that integrates multimodal covariates directly into the forecasting to further improve forecasting performance and employs a two-stage training strategy.
Yu-Han Zhu, Xiangfei Qiu, Han-Yin Cheng et al.
· 0 citations