Papers by Ruisi Su

2 papers
In Plain Sight: Media Bias Through the Lens of Factual Reporting (D19-1)

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Challenge: lexical bias stems from content realization, or how things are said, but other forms of bias stem from content selection and organization.
Approach: They use a dataset to analyze news articles annotated with 1,727 bias spans to investigate informational bias.
Outcome: The proposed model shows that informational bias appears more frequently than lexical bias.
Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation? (2022.findings-acl)

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Challenge: Pre-trained multilingual sequence-to-sequence models like mBART and mT5 can be used to translate low-resource languages, but their practical application is unclear.
Approach: They conduct an empirical experiment in 10 languages to determine what can pre-trained multilingual sequence-to-sequence models like mBART do to translate low-resource languages?
Outcome: The proposed models are robust to domain differences, but translations for unseen and typologically distant languages remain below 3.0 BLEU.

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