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LLMs can now forecast time series data with greater accuracy and interpretability by fusing their reasoning capabilities with traditional time series models in a novel agentic framework.
LLMs, like humans, exhibit a "frequency bias," performing better when prompted and fine-tuned with more common textual expressions.