Papers with LexFit-based WEs

1 papers
LexFit: Lexical Fine-Tuning of Pretrained Language Models (2021.acl-long)

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Challenge: Transformer-based language models implicitly store a wealth of lexical semantic knowledge, but it is non-trivial to extract that knowledge effectively from their parameters.
Approach: They propose to expose and enrich lexical knowledge from transformer-based language models to serve as effective decontextualized word encoders even when fed input words "in isolation"
Outcome: The proposed model outperforms standard static WEs and vanilla LMs in lexical tasks over four established tasks in 8 languages.

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