SOURCE-LINKED INTELLIGENCE
Earth-Agent-Pro: Towards Real-World Full-Chain Earth Observation with Agents
Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare data, perform domain computations, and derive conclusions from runtime evidence. Existing EO agents typically start from supplied observations, while benchmarks typically provide prepared inputs or candidate answers, leaving full-chain open-world EO execution largely untested. We present Earth-Agent-Pro, an execution-adaptive Plan-and-Execute framework using expert-authored skills to constrain planning and runtime tool use. Workflow-centered structu
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T07:41:36.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.