Probing Cross-lingual Transfer of XLM Multi-language Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AR43F6RNZ" target="_blank" >RIV/00216208:11320/25:R43F6RNZ - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186474840&doi=10.1007%2f978-3-031-53555-0_21&partnerID=40&md5=2dd368fbe6cc5fc20da4886433d53fc6" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186474840&doi=10.1007%2f978-3-031-53555-0_21&partnerID=40&md5=2dd368fbe6cc5fc20da4886433d53fc6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-53555-0_21" target="_blank" >10.1007/978-3-031-53555-0_21</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Probing Cross-lingual Transfer of XLM Multi-language Model

Popis výsledku v původním jazyce

This paper investigates the ability of XLM language model to transfer linguistic knowledge cross-lingually, verifying if and to which extent syntactic dependency relationships learnt in a language are maintained in other languages. In detail, a structural probe is developed to analyse the cross-lingual syntactic transfer capability of XLM model and comparison of cross-language syntactic transfer among languages belonging to different families from a typological classification, which are characterised by very different syntactic constructions. The probe aims to reconstruct the dependency parse tree of a sentence in order to representing the input sentences with the contextual embeddings from XLM layers. The results of the experimental assessment improved the previous results obtained using mBERT model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Název v anglickém jazyce

Probing Cross-lingual Transfer of XLM Multi-language Model

Popis výsledku anglicky

This paper investigates the ability of XLM language model to transfer linguistic knowledge cross-lingually, verifying if and to which extent syntactic dependency relationships learnt in a language are maintained in other languages. In detail, a structural probe is developed to analyse the cross-lingual syntactic transfer capability of XLM model and comparison of cross-language syntactic transfer among languages belonging to different families from a typological classification, which are characterised by very different syntactic constructions. The probe aims to reconstruct the dependency parse tree of a sentence in order to representing the input sentences with the contextual embeddings from XLM layers. The results of the experimental assessment improved the previous results obtained using mBERT model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

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

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Advances in Internet, Data & Web Technologies

ISBN

978-3-031-53554-3

Počet stran výsledku

10

Strana od-do

219-228

Počet stran knihy

462

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

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Kód UT WoS kapitoly

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