Papers by Koki Horiguchi

2 papers
Evaluation Dataset for Japanese Medical Text Simplification (2024.naacl-srw)

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Challenge: Existing studies on medical text simplification in English have not been well explored in Japanese because of the lack of a parallel corpus of this domain.
Approach: They propose a lexically constrained reranking method that allows to avoid technical terms to be output.
Outcome: The proposed method improves on the weblogs of Japanese patients and reduces the need for a training corpus.
MultiMSD: A Corpus for Multilingual Medical Text Simplification from Online Medical References (2025.findings-acl)

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Challenge: Medical texts contain technical terms, and non-experts often cannot use information effectively.
Approach: They propose a method for training medical text simplification models to actively paraphrase medical terms.
Outcome: The proposed method improves the performance of medical text simplification in nine languages.

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