Papers by Xinran Han

    1 papers
    Compositional Data and Task Augmentation for Instruction Following (2021.findings-emnlp)

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    Challenge: Existing models that understand spatial concepts and compositional language are inadequate for executing natural language instructions in a physically grounded domain.
    Approach: They propose to use knowledge-free auxiliary signals to help the model understand compositional instructions and provide supervision for the instruction's components.
    Outcome: The proposed model correctly identifies the source block while the existing model fails on this example.

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