Contextualized and Generalized Sentence Representations by Contrastive Self-Supervised Learning: A Case Study on Discourse Relation Analysis (2021.naacl-main)
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| Challenge: | Existing methods to learn contextualized and generalized sentence representations are limited by the size of manually annotated data. |
| Approach: | They propose a method to learn contextualized and generalized sentence representations using contrastive self-supervised learning. |
| Outcome: | The proposed method outperforms baseline methods based on BERT, XLNet, and RoBERTa in English and Japanese and outperformed strong baseline methods. |
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