Papers by Yaocheng Gui

1 papers
DynGL-SDP: Dynamic Graph Learning for Semantic Dependency Parsing (2022.coling-1)

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Challenge: Existing parsers that learn graph representations based on static graphs are error-prone and disjointed . Graph-based parser can parse sentences efficiently but suffer from error propagation .
Approach: They propose a dynamic graph learning framework to learn graph representations based on a static graph constructed by an existing parser.
Outcome: The proposed parser outperforms the previous parsers on the SemEval-2015 task 18 dataset in three languages.

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