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Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents
Vision-language-action and world-action models have demonstrated impressive capabilities in robotics, yet generalization to unseen tasks remains challenging. More recently, general-purpose multimodal agents have shown great potential for zero-shot robotic task solving. However, they often incur high
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