Papers with canonical task

1 papers
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification (2020.emnlp-main)

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Challenge: Text classification is a critical research topic with broad applications in natural language processing. graph neural networks (GNNs) have received increasing attention but their performance is jeopardized in practice.
Approach: They propose a model which captures long-distance interactions between words and a graph-based model which can be used to perform text classification.
Outcome: The proposed model can achieve more expressive power with less computational consumption on the text classification task.

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