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## 🚀 Introduction
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Existing vision-language-action (VLA) models act in 3D real-world but are typically built on 2D encoders, leaving a spatial reasoning gap that limits generalization and adaptability. In this work, we introduce **FALCON (From Spatial to Action)**, a novel paradigm that injects rich 3D spatial tokens into the action head of a VLA model, enabling robust spatial understanding and SOTA performance across diverse manipulation tasks without disrupting vision-language alignment. See our paper at [here](https://arxiv.org/abs/2510.17439).
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# Dataset Card for CALVIN
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## Dataset Details
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## 🚀 Introduction
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Existing vision-language-action (VLA) models act in 3D real-world but are typically built on 2D encoders, leaving a spatial reasoning gap that limits generalization and adaptability. In this work, we introduce **FALCON (From Spatial to Action)**, a novel paradigm that injects rich 3D spatial tokens into the action head of a VLA model, enabling robust spatial understanding and SOTA performance across diverse manipulation tasks without disrupting vision-language alignment. See our paper at [here](https://arxiv.org/abs/2510.17439).
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# Dataset Card for CALVIN Dataset-Camera Parameters
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## Dataset Details
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