Papers with bi-directional language model

1 papers
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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