Papers with relative position embedding methods

1 papers
Improve Transformer Models with Better Relative Position Embeddings (2020.findings-emnlp)

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Challenge: Existing methods for generating position embeddings are not fully utilized in NLP tasks.
Approach: They propose to generalize the absolute position embedding to a generalized relative position embedded method . they also propose to use the relative embeddable method to improve the accuracy of large models .
Outcome: The proposed method improves accuracy on the SQuAD1.1 dataset compared to previous methods . it can be easily adopted as a drop-in replacement for improving accuracy of large models .

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