Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

ArXi:2510.12061v2 Announce Type: replace Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generalize poorly across events, and offer limited interpretability. While Large language models (LLMs) provide few-shot generalization, they remain text-bound and blind to geography. To bridge this gap, we