Papers by Allan Jepson

1 papers
Dependency parsing with structure preserving embeddings (2021.eacl-main)

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Challenge: Modern neural approaches to dependency parsing are trained to predict a tree structure by learning a contextual representation for tokens in a sentence and a head–dependent scoring function.
Approach: They propose to combine a contextual representation for tokens and a head–dependent scoring function to learn interpretable representations by training a parser to explicitly preserve structural properties of a tree.
Outcome: The proposed approach yields strong tree distance preservation and parsing performance on par with a competitive graph-based parser.

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