LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting

Understand

Time Series Forecasting (TSF) has long been a challenge in time series analysis.

• Inspired by the success of Large Language Models (LLMs), researchers are now developing Large Time Series Models (LTSMs)-universal transformer-based models that use autoregressive prediction-to improve TSF.
• However, training LTSMs on heterogeneous time series data poses unique challenges, including diverse frequencies, dimensions, and patterns across datasets.
• Recent endeavors have studied and evaluated various design choices aimed at enhancing LTSM training and generalization capabilities.