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Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AR8ZJDATM" target="_blank" >RIV/00216208:11320/23:R8ZJDATM - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162062605&partnerID=40&md5=920079626a35aa8b4aba8d7cb2b59403" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162062605&partnerID=40&md5=920079626a35aa8b4aba8d7cb2b59403</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

  • Original language description

    "The NLP community has mainly focused on scaling Large Language Models (LLMs) vertically, i.e., making them better for about 100 languages. We instead scale LLMs horizontally: we create, through continued pretraining, Glot500-m, an LLM that covers 511 predominantly low-resource languages. An important part of this effort is to collect and clean Glot500-c, a corpus that covers these 511 languages and allows us to train Glot500-m. We evaluate Glot500-m on five diverse tasks across these languages. We observe large improvements for both high-resource and low-resource languages compared to an XLM-R baseline. Our analysis shows that no single factor explains the quality of multilingual LLM representations. Rather, a combination of factors determines quality including corpus size, script, “help” from related languages and the total capacity of the model. Our work addresses an important goal of NLP research: we should not limit NLP to a small fraction of the world's languages and instead strive to support as many languages as possible to bring the benefits of NLP technology to all languages and cultures. Code, data and models are available at https://github.com/cisnlp/Glot500. © 2023 Association for Computational Linguistics."

  • 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

    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

    "Proc. Annu. Meet. Assoc. Comput Linguist."

  • ISBN

    978-195942972-2

  • ISSN

    0736-587X

  • e-ISSN

  • Number of pages

    36

  • Pages from-to

    1082-1117

  • Publisher name

    Association for Computational Linguistics (ACL)

  • Place of publication

  • Event location

    Melaka, Malaysia

  • Event date

    Jan 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article