Hoiio Kong

Abstract With the development of artificial intelligence, diverse datasets can be assisted in refined operations AI. In recent years, AI has been applied to meteorological data forecasting. However, using AI presents challenges such as long training times and high computational costs. Applying similar meteorological data models across different regions to reduce repetitive training costs remains a significant issue to address.

Submitted: 16 September 2025 Posted: 17 September 2025 You are already at the latest version Trajectory traffic semantic understanding is fundamental to applications such as intelligent transportation and urban mobility analysis. While multimodal large language models (MLLMs) have recently advanced remote sensing scene understanding, current models remain focused on general remote sensing semantics and lack tailored designs for trajectory-specific tasks.

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