Papers with Context-to-Vec

1 papers
Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings (2022.acl-long)

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Challenge: Contextualized embeddings are expensive and resource-demanding, hence environmentally unfriendly.
Approach: They propose a method to convert contextualized embeddings from pre-trained models into static embeddables using synonym knowledge and weighted vector distribution.
Outcome: The proposed method outperforms baseline embeddings by a large margin through extrinsic and intrinsic tasks.

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