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Achieve surprisingly strong imitation learning for robotic lab automation using a model under 500M parameters, demonstrating that you don't need massive models for real-world tasks.
LLMs can plan complex robot tasks with 27% less human input by using a mixture-of-agent system to answer questions and behavior trees to structure execution.
