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MEOX: Compact Multimodal Mixture-of-Experts for Earth Observation

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

Recent advances in Earth Observation representation learning accommodate heterogeneous sensors and missing observations, often through larger architectures. We present MEOX (Multimodal Earth Observation with eXperts), a multimodal masked autoencoder with a 2.939 million-parameter encoder and 3.115 million parameters in total. Sensor-specific adapters, explicit validity signals, and a shared sparse-expert block preserve modality-dependent processing before a learned patch-wise fusion. Four metadata tokens then accompany a single spatial sequence through fourteen further encoder blocks. Shared e

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First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.