Papers by Thomas Effland
Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization (2023.tacl-1)
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| Challenge: | Existing methods for cross-lingual syntactic analysis have been shown to be effective for low-resource languages. |
| Approach: | They propose to use low-order statistical functions to shape model distributions for semi-supervised learning on low-resource datasets. |
| Outcome: | The proposed method improves POS and LAS on 5 target languages and provides significant gains over strong cross-lingual-transfer-plus-fine-tuning baselines for modest amounts of label data. |
Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss (2021.tacl-1)
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| Challenge: | Named entity recognition is a critical subtask of many domain-specific natural language understanding tasks. |
| Approach: | They propose a novel loss to learn named entity recognizers in the presence of missing entity annotations. |
| Outcome: | The proposed approach outperforms state-of-the-art methods in a challenging setting with only 1,000 biased annotations, averaged across 7 datasets. |