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Marvelous Agglutinative Language Effect on Cross Lingual Transfer Learning

arXiv 2204.03831 ↗First posted 8 Apr 2022cs.CLcited by 0

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Abstract (arXiv)

As for multilingual language models, it is important to select languages for training because of the curse of multilinguality. It is known that using languages with similar language structures is effective for cross lingual transfer learning. However, we demonstrate that using agglutinative languages such as Korean is more effective in cross lingual transfer learning. This is a great discovery that will change the training strategy of cross lingual transfer learning.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 17 references that are in the map. First posted on arXiv 8 Apr 2022.

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References · 14

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2 more
  1. 2018Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Modelcited by 46
  2. 2020KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understandingcited by 37

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