DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling (2022.coling-1)
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| Challenge: | a conversational system can learn to rank response candidates for a given dialogue context by computing similarity between their vector representations. |
| Approach: | They propose a framework that incorporates augmented dialogue contexts into the learning objective. |
| Outcome: | The proposed framework outperforms existing methods and is more robust to perturbations seen during inference. |
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