Papers with sequence-to-sequence based baseline models

1 papers
Sequence-to-Sequence Learning for Task-oriented Dialogue with Dialogue State Representation (C18-1)

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Challenge: Existing pipeline models for task-oriented dialogue system require explicit modeling of dialogue states and hand-crafted action spaces to query domain-specific knowledge base.
Approach: They propose a framework that leverages the advantages of classic pipeline and sequence-to-sequence models.
Outcome: The proposed framework outperforms baseline models on automatic and human evaluation on a Stanford Multi-turn Multi-domain task-oriented dialogue dataset.

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