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LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots

LLM-Personalize introduces a framework for personalized LLM planners in household robotics, utilizing imitation learning and iterative self-training to align the planners with human preferences. The framework achieves a substantial success rate improvement over existing solutions, demonstrating enhanced alignment with user preferences in household robotics tasks.

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