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Yueyang Launches Kongyi Large Model for Embodied Intelligence, Standard Task Success Rate Tops 99%

Embodied intelligence has reached a major breakthrough. Robotics company Yuqiang officially unveiled its in-house developed world action model, the "Kongyi DobotWAM" embodied large model, marking a significant step forward in enabling robots to understand and perform complex real-world tasks.
To assess the model's core capabilities, the "Kongyi" embodied large model was rigorously tested on LIBERO, the industry-standard benchmark for embodied intelligence. Results showed that the model successfully completed all four standard task suites: LIBERO-Spatial, LIBERO-Object, LIBERO-Goal, and LIBERO-10.
The four task suites precisely cover the essential dimensions of embodied intelligence. In practice, the Kongyi model demonstrated strong stability and accuracy in spatial understanding, object generalization, goal instruction comprehension, and long-term task execution, achieving an overall average success rate of 99.25%. This performance not only confirms the technical maturity of this world action model in handling complex physical interactions but also positions it to deliver robust foundational support for the commercial adoption of embodied intelligence across the industry.
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Embodied intelligence has reached a major breakthrough. Robotics company Yuqiang officially unveiled its in-house developed world action model, the "Kongyi DobotWAM" embodied large model, marking a significant step forward in enabling robots to understand and perform complex real-world tasks.
To assess the model's core capabilities, the "Kongyi" embodied large model was rigorously tested on LIBERO, the industry-standard benchmark for embodied intelligence. Results showed that the model successfully completed all four standard task suites: LIBERO-Spatial, LIBERO-Object, LIBERO-Goal, and LIBERO-10.
The four task suites precisely cover the essential dimensions of embodied intelligence. In practice, the Kongyi model demonstrated strong stability and accuracy in spatial understanding, object generalization, goal instruction comprehension, and long-term task execution, achieving an overall average success rate of 99.25%. This performance not only confirms the technical maturity of this world action model in handling complex physical interactions but also positions it to deliver robust foundational support for the commercial adoption of embodied intelligence across the industry.
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