A hybrid multi-agent orchestrator (composition plus iterative reassessment) reports 60.3% agentic correctness on generated remote sensing workflows, about 17 percentage points above the single-agent GeoLLM-Engine baseline.
Geochat: Grounded large vision-language model for remote sensing,
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Multi-Agent Geospatial Copilots for Remote Sensing Workflows
A hybrid multi-agent orchestrator (composition plus iterative reassessment) reports 60.3% agentic correctness on generated remote sensing workflows, about 17 percentage points above the single-agent GeoLLM-Engine baseline.