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Integrating dynamic meteorological semantics with a self-evolving retrieval framework boosts precipitation estimation accuracy in radar-sparse regions.
Forget fine-tuning: this training-free pipeline aligns VLMs with human preferences by calibrating concept scores, outperforming supervised methods in urban perception tasks.
