Papers with nonparametric masked language model

1 papers
Nonparametric Masked Language Modeling (2023.findings-acl)

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Challenge: Existing language models (LMs) predict tokens with a softmax over a finite vocabulary, which can make it difficult to predict rare tokens or phrases.
Approach: They introduce a nonparametric masked language model that replaces a softmax with a distribution over every phrase in a reference corpus and uses an in-batch approximation to train it.
Outcome: The proposed model outperforms larger parametric models on 16 tasks including classification, fact probing and question answering.

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