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Specializing Multilingual Language Models: An Empirical Study

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10442245" target="_blank" >RIV/00216208:11320/21:10442245 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Specializing Multilingual Language Models: An Empirical Study

  • Original language description

    Pretrained multilingual language models have become a common tool in transferring NLP capabilities to low-resource languages, often with adaptations. In this work, we study the performance, extensibility, and interaction of two such adaptations: vocabulary augmentation and script transliteration. Our evaluations on part-of-speech tagging, universal dependency parsing, and named entity recognition in nine diverse low-resource languages uphold the viability of these approaches while raising new questions around how to optimally adapt multilingual models to low-resource settings.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 1st Workshop on Multilingual Representation Learning

  • ISBN

    978-1-954085-96-1

  • ISSN

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    51-61

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Stroudsburg

  • Event location

    Punta Cana

  • Event date

    Nov 11, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article