Papers with disentangled learning

1 papers
Disentangling Language and Knowledge in Task-Oriented Dialogs (N19-1)

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Challenge: Existing approaches to handle task-oriented dialogs break when asked to handle such changes.
Approach: They propose an encoder-decoder architecture with a novel Bag-of-Sequences memory which facilitates the disentangled learning of the response’s language model and its knowledge incorporation.
Outcome: The proposed architecture outperforms state-of-the-art models on bAbI OOV test sets and other human-human datasets and shows that it is robust to KB modifications.

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