Researchers from CMU and NYU Propose LLMTime: An Artificial Intelligence Method for Zero-Shot Time Series Forecasting with Large Language Models (LLMs)

Despite having some parallels to other sequence modeling issues, like text, audio, or video, time series has two characteristics that make it particularly difficult. Aggregated time series datasets frequently include sequences from drastically varied sources, occasionally with missing values, in contrast to video or audio, which normally have uniform input scales and sample rates. Furthermore, […]

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