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You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10476179" target="_blank" >RIV/00216208:11320/23:10476179 - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2023.sigtyp-1.1.pdf" target="_blank" >https://aclanthology.org/2023.sigtyp-1.1.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.18653/v1/2023.sigtyp-1.1" target="_blank" >10.18653/v1/2023.sigtyp-1.1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models

  • Original language description

    Multilingual models have been widely used for the cross-lingual transfer to low-resource languages. However, the performance on these languages is hindered by their under-representation in the pretraining data. To alleviate this problem, we propose a novel multilingual training technique based on teacher-student knowledge distillation. In this setting, we utilize monolingual teacher models optimized for their language. We use those teachers along with balanced (sub-sampled) data to distill the teachers&apos; knowledge into a single multilingual student. Our method outperforms standard training methods in low-resource languages and retains performance on high-resource languages while using the same amount of data. If applied widely, our approach can increase the representation of low-resource languages in NLP systems.

  • 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

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • 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 5th Workshop on Research in Computational Linguistic Typology and Multilingual NLP

  • ISBN

    978-1-959429-56-2

  • ISSN

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    1-11

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Stroudsburg, PA, USA

  • Event location

    Dubrovnik, Croatia

  • Event date

    May 2, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article