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The University of Hong Kong 2 XPENG Robotics
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Action-Grounded Representation Alignment (AGRA) transforms how robots interpret visual data, enabling them to focus on crucial interaction regions and significantly enhancing manipulation performance.
State-dependent action constraints can be effectively managed in DRL, leading to near-optimal solutions in complex queueing networks.
Capturing structured relationships in images can boost open-vocabulary object detection performance by over 10% on novel categories.
