Papers by Keita Fukushima

1 papers
Disentangling Meaning and Language Components in Diverse Multilingual Sentence Embeddings (2026.acl-srw)

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Challenge: Existing studies have reported language specificity in multilingual sentence embeddings, resulting in language-specific subspaces.
Approach: They propose to disentangle multilingual sentence embeddings into language-dependent and language-agnostic components to improve cross-lingual similarity estimation.
Outcome: The proposed methods improve cross-lingual similarity estimation across multiple embeddings.

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