Feb. 6, 2024, 5:45 a.m. | Dilxat Muhtar Zhenshi Li Feng Gu Xueliang Zhang Pengfeng Xiao

cs.LG updates on arXiv.org arxiv.org

The revolutionary capabilities of large language models (LLMs) have paved the way for multimodal large language models (MLLMs) and fostered diverse applications across various specialized domains. In the remote sensing (RS) field, however, the diverse geographical landscapes and varied objects in RS imagery are not adequately considered in recent MLLM endeavors. To bridge this gap, we construct a large-scale RS image-text dataset, LHRS-Align, and an informative RS-specific instruction dataset, LHRS-Instruct, leveraging the extensive volunteered geographic information (VGI) and globally available …

applications bot capabilities cs.ai cs.cv cs.lg diverse diverse applications domains language language model language models large language large language models llms mllm mllms multimodal objects sensing

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