Preprint
Aug 2026
REATS: LLM Reasoning-based Ensemble Learning for Adaptive Time Series Forecasting
REATS is proposed, which leverages LLM reasoning capabilities as an intelligent ensemble router that jointly processes textual temporal pattern descriptions and numerical features to produce interpretable, sample-adaptive ensemble weights through chain-of-thought reasoning.
Xu Zhang, Chang Xu, Hui Sun et al.
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