arXiv (OAI Expanded)
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Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining
Applying an imitation learning policy to a new manipulation task usually requires collecting new demonstrations and retraining the model, which makes sample efficiency a practical concern. Pretraining on large-scale robot datasets is effective in this respect, but such datasets are costly to collect
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