Papers with interpretability issue of task-oriented dialogue systems

1 papers
An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation (2022.acl-long)

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Challenge: Existing approaches to interpret task-oriented dialogue systems employ an implicit reasoning strategy that makes the model predictions uninterpretable to humans.
Approach: They propose a neuro-symbolic approach that performs explicit reasoning that justifies model decisions by reasoning chains.
Outcome: The proposed approach achieves better results and introduces an interpretable decision process.

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