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October 1, 2025Open Access

LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning

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LAPP integrates large language models for efficient preference prediction in robot learning tasks.
It enables robots to learn complex skills with reduced human involvement and improved performance metrics.
The preference labels generated guide policy optimization, leading to precise control in behavior execution.
LAPP shows promise in enabling scalable robotic learning, particularly in challenging tasks like dynamic locomotion.

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This framework improves preference prediction in reinforcement learning, enhancing robotic behavior acquisition.

Jian et al. (2025) studied this question.

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