Papers by Rilyn Han

1 papers
Rethinking Efficient Multilingual Text Summarization Meta-Evaluation (2024.findings-acl)

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Challenge: a limited number of human annotations are required to evaluate multilingual summarization evaluation metrics.
Approach: They propose a multilingual meta-evaluation framework that uses machine translation systems to transform a monolingual metaevaluations dataset into multilingual versions.
Outcome: The proposed framework outperforms classical text-matching-based metrics in non-English languages.

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