Papers by Seiji Sugiyama

1 papers
Paraphrase-based Contrastive Learning for Sentence Pair Modeling (2025.naacl-srw)

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Challenge: Existing methods to improve performance of sentence pair modeling are not available on a large-scale for non-English languages.
Approach: They propose a method to apply contrastive learning to pre-trained masked language models . they use sentence embeddings of paraphrase pairs to make similar sentences .
Outcome: The proposed method can be used on four sentence pair modeling tasks in English and Japanese.

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