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• LinkS²Bench is the first comprehensive benchmark designed to evaluate VLMs' wide-area, dynamic cross-view spatial intelligence.method 95%
• Existing benchmarks are confined to isolated UAV videos or static satellite imagery, failing to evaluate dynamic local-to-global spatial mapping.limitation 90%
• LinkS²Bench links 1,022 minutes of dynamic UAV footage with high-resolution satellite imagery covering over 200 km².method 95%
• Evaluations of 18 representative VLMs reveal a substantial performance gap compared to human baselines.result 90%
• Accurate cross-view dynamic alignment is identified as the critical bottleneck for VLMs in this domain.result 85%
• A Cross-View Alignment Adapter, designed to provide explicit alignment, significantly improves model performance.technical 90%
• Fine-tuning experiments underscore the potential of LinkS²Bench in advancing VLM adaptation for complex spatial reasoning.result 85%
• The capacity of Vision-Language Models (VLMs) to master the complex interplay between UAV and satellite spatial intelligence remains largely unexplored prior to this work.limitation 80%

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