Shypd.aiThe largest open index of AI toolsX-VLA is an open-source research tool that implements a soft-prompted transformer for scalable cross-embodiment vision-language-action models. It enables state-of-the-art generalization across diverse robotic platforms.
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X-VLA is the official implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model," accepted to ICLR 2026. This open-source project introduces a soft prompt mechanism using embodiment-specific learnable embeddings to guide a unified Transformer backbone. This approach facilitates effective multi-domain policy learning across heterogeneous large-scale robot datasets. The resulting X-VLA-0.9B architecture demonstrates state-of-the-art generalization across six simulation platforms and three real-world robots, outperforming previous VLA methods in dexterity, adaptability, and efficiency. It supports a Server–Client architecture for distributed inference and offers various pre-trained models fine-tuned for specific robotic embodiments and benchmarks like AgiBot World Challenge, CALVIN, Google Robot, and LIBERO.
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