A two-stage fine-tuning framework with instance-level semantic fusion lets language-conditioned robots learn object-arrangement tasks from a few demonstrations and generalize to unseen environments.
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Improving Generalization of Language-Conditioned Robot Manipulation
A two-stage fine-tuning framework with instance-level semantic fusion lets language-conditioned robots learn object-arrangement tasks from a few demonstrations and generalize to unseen environments.