Papers with contextualized word embedding
Leveraging Three Types of Embeddings from Masked Language Models in Idiom Token Classification (2022.starsem-1)
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| Challenge: | Recent research shows that contextualized word embeddings can give promising results for idiom token classification. |
| Approach: | They propose to leverage contextualized word embeddings from masked language models to improve idiom token classification. |
| Outcome: | The proposed method improves idiom token classification for English and Japanese datasets. |
Pooled Contextualized Embeddings for Named Entity Recognition (N19-1)
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| Challenge: | Contextual string embeddings are a recent type of word embeddable that are useful for sequence labeling tasks. |
| Approach: | They propose a method that dynamically aggregates contextualized embeddings of each unique string . they then use a pooling operation to distill a ”global” word representation from all contextualized instances . |
| Outcome: | The proposed method improves state-of-the-art for named entity recognition tasks. |