Papers by Ying-xin Wu

1 papers
Knowledge-Aware Meta-learning for Low-Resource Text Classification (2021.emnlp-main)

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Challenge: Existing meta-learning techniques may not be well-suited to testing tasks when they are not well-supported by training tasks.
Approach: They propose to use a meta-learning algorithm to add representations for each sentence learned from the extracted sentence-specific knowledge graph.
Outcome: The proposed model is able to represent each sentence learned from the extracted knowledge graph under supervised adaptation and unsupervised adaptation settings.

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