Papers by Amelia Archer

1 papers
Small and Practical BERT Models for Sequence Labeling (D19-1)

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Challenge: Existing models for morphosyntactic tagging have focused on building separate models for each language or for a small group of related languages.
Approach: They propose a scheme to train a single multilingual sequence labeling model that is small and fast enough to run on a CPU.
Outcome: The proposed model outperforms state-of-the-art models on low-resource languages and low-level models on codemixed inputs.

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