Papers with rethinking mechanism

1 papers
Learning to Prune Dependency Trees with Rethinking for Neural Relation Extraction (2020.coling-main)

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Challenge: Existing approaches to remove noise from dependency trees are not optimal due to complexity and variability of natural language.
Approach: They propose a dynamically pruned Graph Convolutional Network (DP-GCN) that prunes the dependency tree with rethinking in an end-to-end scheme.
Outcome: The proposed model achieves impressive results compared to strong competitors.

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