Diversifying Reply Suggestions Using a Matching-Conditional Variational Autoencoder (N19-2)
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| Challenge: | Automated reply suggestions (SR) are becoming common in many popular applications such as Gmail (2016) . |
| Approach: | They propose a constrained-sampling approach to make the variational inference efficient for a commercial instant-messaging system. |
| Outcome: | The proposed model increases diversity without losing relevance in offline experiments. |
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| Challenge: | Existing models for multilingual RS are limited by capacity and data distribution skew . we propose Conditional Generative Matching models (CGM) to overcome these challenges . |
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| Challenge: | Existing methods to generate questions based on answers and relevant contexts are not suitable for all questions . |
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