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StateSkill-Agent: An Effective and Efficient Embodied Agent via State-conditioned Skill
In this work, we aim to develop an embodied MLLM agent that understands and solves embodied tasks by learning, abstracting, and reusing transferrable and generalizable behavioral patterns. To this end, we propose StateSkill, a new skill representation for embodied agents, which introduces the concep
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