Papers by Xiaochun Ma

1 papers
Graph-Based Semi-Supervised Learning for Natural Language Understanding (D19-53)

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Challenge: Semi-supervised learning is an efficient method to augment training data from unlabeled data.
Approach: They propose semi-supervised learning models and their inductive variants for NLU and use them to find similar utterances and construct a graph.
Outcome: The proposed model improves the error rate of the model by 5% using publicly available NLU data and models.

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