Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations (N18-2)
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| Challenge: | Neural network-based models for NLP have been growing with state-of-the-art results in various tasks. |
| Approach: | They propose a data augmentation method for labeled sentences called contextual augmentation. |
| Outcome: | The proposed method improves classifiers based on convolutional or recurrent neural networks. |
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| Challenge: | Recent approaches to identify metaphors ignore extra information from data, such as contextual information and broader discourse information. |
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| Challenge: | Existing approaches to augment training data are limited or marginal, or even diminishing or adverse especially given original training corpus is relatively sufficient or the backbone classifiers are PLM based. |
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