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Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs
Similarity-based retrieval is the dominant rule for conditioning large language models (LLMs) in in-context learning, retrieval-augmented generation, and prompt-based time series forecasting. The rule concentrates on near-duplicate candidates, an issue that has motivated diversity-aware retrieval bu
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