AirGPT: pioneering the convergence of conversational AI with atmospheric science
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Abstract
Large language models (LLMs) face significant limitations in specialized scientific domains due to their inability to perform data analysis and their tendency to generate inaccurate information. This challenge is particularly critical in air quality management, where precise analysis is essential for addressing climate change and pollution control initiatives. To bridge this gap, we present AirGPT, a computational framework that integrates conversational AI with atmospheric science expertise through a curated corpus of peer-reviewed literature and specialized data analysis capabilities. Through a novel architecture combining natural language processing and domain-specific analytical tools, AirGPT achieved…
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44
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- FWCI
- 23.15
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3Topics & keywords
Topics
Keywords
- Convergence (economics)
- Computer science
- Environmental science
- Mathematics education
- Psychology
- Economics
UN Sustainable Development Goals
- Climate action
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