Papers by Christopher Jenkins

1 papers
To Split or Not to Split: Composing Compounds in Contextual Vector Spaces (2023.emnlp-main)

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Challenge: Contextual word embedding models rely on sub-word tokenization to represent single orthographic words but are often suboptimal in under-resourced contexts.
Approach: They propose to use a masked language modelling task to evaluate the model's performance . they use re-trained tokenizers to pre-split compounds into constituents .
Outcome: The proposed models improve on the masked language modelling task and compositionality prediction by pre-splitting compounds into constituents.

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