Papers with contextual representation of target words

1 papers
CATE: A Contrastive Pre-trained Model for Metaphor Detection with Semi-supervised Learning (2021.emnlp-main)

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Challenge: Existing models for metaphor detection require a large amount of labeled data and are not linguistically-based.
Approach: They propose a ContrAstive pre-Trained modEl (CATE) for metaphor detection with semi-supervised learning using a pre-trained model to obtain a contextual representation of target words.
Outcome: The proposed model outperforms existing models on several benchmark datasets and achieves better performance against state-of-the-art models.

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