Incremental Sense Weight Training for the Interpretation of Contextualized Word Embeddings

Jiang Xinyi
Jiang Xinyi
Yang Zhengzhe
Yang Zhengzhe
Cited by: 0|Views15

Abstract:

We present a novel online algorithm that learns the essence of each dimension in word embeddings by minimizing the within-group distance of contextualized embedding groups. Three state-of-the-art neural-based language models are used, Flair, ELMo, and BERT, to generate contextualized word embeddings such that different embeddings are ge...More

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