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A single generalist model outperforms specialized systems, achieving over 35% improvement in real-world robotic task success.
SpatialClaw enables agents to dynamically compose and adapt their reasoning strategies, achieving a remarkable 11.2-point accuracy boost over traditional spatial agents.
