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		<title>Semantic Labels Guide Terrain-Specific Humanoid Behavior in Simulation</title>
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		<pubDate>Mon, 26 Oct 2026 21:11:56 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Behavior]]></category>
		<category><![CDATA[Behavior Cloning]]></category>
		<category><![CDATA[humanoid robotics]]></category>
		<category><![CDATA[locomotion]]></category>
		<category><![CDATA[multi-modal]]></category>
		<category><![CDATA[multimodal learning]]></category>
		<category><![CDATA[Reinforcement Learning]]></category>
		<category><![CDATA[robot simulation]]></category>
		<category><![CDATA[semantic conditioning]]></category>
		<category><![CDATA[semantic-conditioned]]></category>
		<category><![CDATA[terrain adaptation]]></category>
		<category><![CDATA[Unitree H1]]></category>
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					<description><![CDATA[A simulator study found that semantic terrain labels guided a unified behavior-cloning policy to select flat-ground and stairway behaviors for the Unitree H1 humanoid.]]></description>
		
		
		
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