Align-RAG: Alignment Is All You Need for TSFM In-Context Learning

Retrieval-augmented forecasting promises to adapt frozen Time Series Foundation Models (TSFMs) to new domains without fine-tuning, but recent methods typically rely on learned fusion modules, i.e., trained adapters that merge retrieved examples into the backbone's forecast, based on the assumption that frozen backbones cannot dynamically incorporate retrieved context on their own. We show this assumption is unnecessary. We introduce Align-RAG, a training-free method that applies a closed-form pe

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ethics.ai (6 August 2026), “Align-RAG: Alignment Is All You Need for TSFM In-Context Learning,” evidence record 17395, https://ethics.ai/record/17395 (originally published by arXiv cs.LG).

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