Papers with counter-fitted embedding injection

1 papers
GiBERT: Enhancing BERT with Linguistic Information using a Lightweight Gated Injection Method (2021.findings-emnlp)

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Challenge: Recent pre-trained language models such as BERT have led to noticeable improvements in semantic similarity detection.
Approach: They propose to explicitly inject linguistic information in the form of word embeddings into any layer of a pre-trained BERT.
Outcome: The proposed method improves on multiple semantic similarity datasets and shows that it is beneficial and currently missing from the original model.

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