Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots (D19-1)
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| Challenge: | Existing models for personalized dialogues rank responses according to their semantic relevance with the given context. |
| Approach: | They propose a dually interactive matching network (DIM) for presenting personalities of dialogue agents in retrieval-based chatbots. |
| Outcome: | The proposed model outperforms the existing model by 14.5% and 27.7% on a PERSONA-CHAT dataset. |
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| Challenge: | Existing approaches to personalized dialogue generation rely on dialogue data paired with user traits, profiles or persona description sentences. |
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| Challenge: | Currently, retrieval-based dialogues are performed in shallow ways . a recent study investigated the problem of context-response matching in open-domain . |
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| Challenge: | Existing systems that focus on persona do not explore well the correlation between persona and empathy. |
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| Challenge: | a plug-and-play persona prompting system can be used to generate personalized responses for real applications . a recent study shows that dialog context alone is insufficient for personalized response selection . |
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| Challenge: | Existing methods for multi-turn response selection are not practical as the turns of conversations vary. |
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