Papers with Answering real-world geospatial questions

1 papers
Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questions (2026.findings-acl)

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Challenge: Existing large language models lack spatial computing capabilities and access to up-to-date geospatial data.
Approach: They propose a Retrieval-Augmented Generation framework for geospatial question answering . it integrates structured spatial databases with LLMs via a hybrid spatial retriever .
Outcome: Experiments show that Spatial-RAG significantly improves over baselines.

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