Papers by Jason Jo

1 papers
Compositional Generalization by Factorizing Alignment and Translation (2020.acl-srw)

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Challenge: a crucial property underlying the expressive power of human language is its systematicity.
Approach: They propose to make an analogous separation between alignment and translation in neural machine translation to capture compositional structure.
Outcome: The proposed architecture outperforms existing neural networks on a compositional generalization task without supervision.

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