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Found 2 papers, 1 papers with code
Finetuning Offline World Models in the Real World
In this work, we seek to get the best of both worlds: we consider the problem of pretraining a world model with offline data collected on a real robot, and then finetuning the model on online data collected by planning with the learned model.
Deep learning in a bilateral brain with hemispheric specialization
We took a different approach and aimed to understand how dual hemispheres in a bilateral architecture interact to perform well in a given task.
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