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1
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance
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2
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification
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3
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context
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4
Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking
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5
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts
Schütze, Hinrich; Schick, Timo. - : Ludwig-Maximilians-Universität München, 2019
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