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GRAM: Correcting Frozen Time-Series Foundation Models via Graph-Retrieved Amplitude Memory
Time-series foundation models (TSFMs) enable zero-shot forecasting through large-scale cross-domain pretraining, while retrieval augmentation further improves their performance by leveraging historical information. However, existing methods typically correct TSFM forecasts using the ground-truth fut
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