Papers by Xinyue Hu

1 papers
RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction (2022.emnlp-main)

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Challenge: Existing approaches focus on minimizing distances between words in aligned pairs, while suffering from low discriminative capability to distinguish the relative orders between positive and negative candidates.
Approach: They propose a ranking-oriented induction model to learn personalized mapping function for each word.
Outcome: The proposed model can learn personalized mapping function for each word on public datasets including rich-resource and low-resourced languages.

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