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Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
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Geospatial foundation models seem to handily beat standard satellite features on remote sensing benchmarks鈥攗ntil you enforce a 10 km spatial buffer, which virtually erases their statistical advantage.
Pretraining loss is a misleading metric, leading to inefficient compute use, while a simple scaling rule can unlock superior performance in pixel-wise Earth-observation models.
