Graph-to-Graph Transformer for Transition-based Dependency Parsing (2020.findings-emnlp)
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| Challenge: | Existing models for conditioning on graphs and predicting graphs are weak, but they are effective for transition-based dependency parsing. |
| Approach: | They propose a Transformer architecture for conditioning on and predicting arbitrary graphs. |
| Outcome: | The proposed architecture outperforms the state-of-the-art in transition-based dependency parsing on English Penn Treebank and 13 languages of Universal Dependencies Treebanks. |
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