5 papers
MetaCaster: Meta-Harness-Optimized Agent for End-to-End Few-Shot Learning of Lightweight Time Series Forecasters
ChengAo Shen, Wenchao Yu, Fangyu Wu +6
Time series forecasting (TSF) is evolving toward multimodal and agentic settings, yet using foundation models remains uneconomical in resource-constrained scenarios, where compact,…
xTime: Extreme Event Prediction with Hierarchical Knowledge Distillation and Expert Fusion
Quan Li, Wenchao Yu, Suhang Wang +4
Extreme events frequently occur in real-world time series and often carry significant practical implications. In domains such as climate and healthcare, these events, such as flood…
Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
ChengAo Shen, Wenchao Yu, Ziming Zhao +4
Time series, typically represented as numerical sequences, can also be transformed into images and texts, offering multi-modal views (MMVs) of the same underlying signal. These MMV…
Multi-modal Time Series Analysis: A Tutorial and Survey
Yushan Jiang, Kanghui Ning, Zijie Pan +7
Multi-modal time series analysis has recently emerged as a prominent research area in data mining, driven by the increasing availability of diverse data modalities, such as text, i…
Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook
Ming Jin, Yaxuan Kong, Yuxuan Liang +13
Temporal data, including time series and spatio-temporal data, are pervasive in real-world applications. Generated in massive volumes by physical and virtual sensors, they record d…