Papers with model Self-Attention Graph Residual Convolution Networks

1 papers
Self-Attention Graph Residual Convolutional Networks for Event Detection with dependency relations (2021.findings-emnlp)

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Challenge: Existing methods to classify events using syntactic dependency relations have not been developed.
Approach: They propose a model which combines syntactic dependency relations with attention-based dynamic tensors to mine node-to-node latent dependency relations via self-attention mechanism.
Outcome: The proposed model improves on the ACE2005 dataset and compares with baseline models.

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