| Challenge: | Existing methods for dialog routing are mostly heuristic and cannot achieve high-quality performance. |
| Approach: | They propose a multi-task learning framework with a dialog encoder and two tailored gated mechanism modules to solve this problem. |
| Outcome: | The proposed model can play the role of hierarchical information filtering and is non-invasive to existing dialog systems. |
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| Challenge: | Existing approaches to multitask learning share the features without distinguishing the usefulness of the features, generating undesired interference between tasks. |
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End-to-End Learning of Task-Oriented Dialogs (N18-4)
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Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System (2022.acl-long)
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Multi-Grained Knowledge Retrieval for End-to-End Task-Oriented Dialog (2023.acl-long)
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| Challenge: | Existing systems blend knowledge retrieval with response generation and optimize them with direct supervision from reference responses. |
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