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Language models exhibit a surprising bias towards cities with expansive infrastructure and rapid growth, revealing their implicit urban assumptions.
Integrating dynamic meteorological semantics with a self-evolving retrieval framework boosts precipitation estimation accuracy in radar-sparse regions.
