Papers by Changmin Seo
Ranking-Enhanced Unsupervised Sentence Representation Learning (2023.acl-long)
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Yeon Seonwoo, Guoyin Wang, Changmin Seo, Sajal Choudhary, Jiwei Li, Xiang Li, Puyang Xu, Sunghyun Park, Alice Oh
| Challenge: | Unsupervised sentence representation learning has progressed through contrastive learning and data augmentation methods such as dropout masking. |
| Approach: | They propose a novel unsupervised sentence encoder, RankEncoder, which predicts the semantic vector of an input sentence by leveraging its relationship with other sentences in an external corpus. |
| Outcome: | The proposed unsupervised sentence encoder achieves 80.07% Spearman’s correlation, a 1.1% improvement over the previous state-of-the-art system. |