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Second is a generalizable embodied foundation model for home scenarios. In response to the multi-step, highly compositional, and strongly long-tailed nature of home tasks, Nuoyin moves beyond traditional imitation-learning frameworks. With innovative model architectures and training methods, it emphasizes modeling task structure, skill composition, and the execution feedback loop—enabling deep understanding and strongly generalizable execution for complex, multi-step household tasks. This allows robots to maintain more stable perception, planning, and execution capabilities in diverse and dynamically changing home environments, while also ensuring safe interaction and controllability.