A survey of multilingual large language models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AQRA9AWJT" target="_blank" >RIV/00216208:11320/26:QRA9AWJT - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.patter.2024.101118" target="_blank" >http://dx.doi.org/10.1016/j.patter.2024.101118</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.patter.2024.101118" target="_blank" >10.1016/j.patter.2024.101118</a>
Alternative languages
Result language
angličtina
Original language name
A survey of multilingual large language models
Original language description
Multilingual large language models (MLLMs) leverage advanced large language models to process and respond to queries across multiple languages, achieving significant success in polyglot tasks. Despite these breakthroughs, a comprehensive survey summarizing existing approaches and recent developments remains absent. To this end, this paper presents a unified and thorough review of the field, highlighting recent progress and emerging trends in MLLM research. The contributions of this paper are as follows. (1) Extensive survey: to our knowledge, this is the pioneering thorough review of multilingual alignment in MLLMs. (2) Unified taxonomy: we provide a unified framework to summarize the current progress in MLLMs. (3) Emerging frontiers: key emerging frontiers are identified, alongside a discussion of associated challenges. (4) Abundant resources: we collect abundant open-source resources, including relevant papers, data corpora, and leaderboards. We hope our work can provide the community quick access and spur breakthrough research in MLLMs. © 2024 The Author(s)
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Patterns
ISSN
2666-3899
e-ISSN
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Volume of the periodical
6
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
30
Pages from-to
1-30
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85214322083