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1 papers
imapScore: Medical Fact Evaluation Made Easy (2024.findings-acl)

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Challenge: Automated evaluation of natural language generation tasks fails to focus on medical QA because of the diversity in medical terminology.
Approach: They propose a new data structure, imap, to capture key information in questions and answers.
Outcome: The proposed model outperforms state-of-the-art metrics in correlation with human scores.

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