Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …

Earth Observation (EO) systems are crucial for cartography, disaster surveillance, and
resource administration. Nonetheless, they encounter considerable obstacles in the …

The advanced function-calling capabilities of foundation models open up new possibilities
for deploying agents to perform complex API tasks. However, managing large amounts of …

State-of-the-art sequential reasoning in Large Language Models (LLMs) has expanded the
capabilities of Copilots beyond conversational tasks to complex function calling, managing …

Large language models (LLMs) are being used in data science code generation tasks, but
they often struggle with complex sequential tasks, leading to logical errors. Their application …

In this preliminary study, we investigate a GPT-driven intent-based reasoning approach to
streamline tool selection for large language models (LLMs) aimed at system efficiency. By …

As machine learning increasingly becomes a crucial tool for geospatial data analysis,
finding and deploying a suitable model presents significant challenges, including the need …

We present GeoLLM-Squad, a geospatial Copilot that introduces the novel multi-agent
paradigm to remote sensing (RS) workflows. Unlike existing single-agent approaches that …

As Large Language Models (LLMs) broaden their capabilities to manage thousands of API
calls, they are confronted with complex data operations across vast datasets with significant …