Papers by Erica K. Shimomoto

2 papers
Multilingual Definition Modeling (2025.findings-acl)

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Challenge: Existing definition modeling tasks are mainly encoder-decoder-based, with no explicit definitions.
Approach: They propose a multilingual study on definition modeling using monolingual dictionary data for four new languages.
Outcome: The proposed task is based on monolingual dictionary data for four new languages . results show that multilingual models can perform on-pair with English but cannot leverage potential cross-lingual synergies .
Hype or not? Formalizing Automatic Promotional Language Detection in Biomedical Research (2026.eacl-long)

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Challenge: Promotional language is a term used to undermine objective evaluation of evidence, impede research development, and erode trust in science.
Approach: They propose formalized guidelines for identifying hype language and apply them to annotate a portion of the National Institutes of Health grant application corpus.
Outcome: The proposed guidelines can help humans reliably annotate candidate hype adjectives and train machine learning models yield promising results.

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