Language pretraining builds a generalizable manifold that supports cross-modal transfer to time series forecasting through linear probes, retrieval, and low-dimensional finetuning alignment.
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LLM Pretraining Shapes a Generalizable Manifold: Insights into Cross-Modal Transfer to Time Series
Language pretraining builds a generalizable manifold that supports cross-modal transfer to time series forecasting through linear probes, retrieval, and low-dimensional finetuning alignment.