An iterative multi-agent prompting loop that applies Tobler's first law of geography improves LLM accuracy and reduces geographic bias on four geospatial estimation tasks across four models, but key details and baselines are missing.
Large language models are geographically biased
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GeoSR: Cognitive-Agentic Framework for Probing Geospatial Knowledge Boundaries via Iterative Self-Refinement
An iterative multi-agent prompting loop that applies Tobler's first law of geography improves LLM accuracy and reduces geographic bias on four geospatial estimation tasks across four models, but key details and baselines are missing.