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Found 2 papers, 1 papers with code
Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
Preference-based reinforcement learning (PbRL) aligns a robot behavior with human preferences via a reward function learned from binary feedback over agent behaviors.
Large Language Models as Generalizable Policies for Embodied Tasks
We show that large language models (LLMs) can be adapted to be generalizable policies for embodied visual tasks.
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