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In this setting, neural operators trained to minimize squared error losses, while capable of accurate short-term forecasts, often fail to reproduce statistical or structural properties of the dynamics over longer time horizons and can yield degenerate results.

Pre-trained large language models (LLMs) based on Transformer have demonstrated striking in-context learning (ICL) abilities.