LLMPred improves LLM-based forecasting by frequency-decomposing inputs and adding an MLP post-processor, but the reported gains largely reflect the trained post-processor and a narrowed multivariate comparison rather than pure zero-shot LLM ability.
Selection of the most suit able decomposition filter for the mea- surement of fluctuating harmonics
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Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting
LLMPred improves LLM-based forecasting by frequency-decomposing inputs and adding an MLP post-processor, but the reported gains largely reflect the trained post-processor and a narrowed multivariate comparison rather than pure zero-shot LLM ability.