Papers with attention-based relational graph convolutional neural network

1 papers
Attention-based Relational Graph Convolutional Network for Target-Oriented Opinion Words Extraction (2021.eacl-main)

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Challenge: empirical results show that our model significantly outperforms all existing models on four benchmark datasets.
Approach: They propose a novel attention-based relational graph convolutional neural network to exploit syntactic information over dependency graphs.
Outcome: The proposed model outperforms existing models on four benchmark datasets.

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