Topic-relevant Response Generation using Optimal Transport for an Open-domain Dialog System (2020.coling-main)
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| Challenge: | Conventional neural generative models generate safe and generic responses which have little connection with previous utterances semantically and would disengage users in a dialog system. |
| Approach: | They propose a method that employs topical constraint and semantic constraint to generate relevant responses by regularizing the decoding objective function with semantic distance. |
| Outcome: | The proposed method generates more topic-relevant and content-rich responses than conventional models. |
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