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Romanian Multiword Expression Detection Using Multilingual Adversarial Training and Lateral Inhibition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ANJN76SBY" target="_blank" >RIV/00216208:11320/23:NJN76SBY - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161461930&partnerID=40&md5=e9d60a8caf5041520b5966a5dbebdf2c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161461930&partnerID=40&md5=e9d60a8caf5041520b5966a5dbebdf2c</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Romanian Multiword Expression Detection Using Multilingual Adversarial Training and Lateral Inhibition

  • Original language description

    "Multiword expressions are a key ingredient for developing large-scale and linguistically sound natural language processing technology. This paper describes our improvements in automatically identifying Romanian multiword expressions on the corpus released for the PARSEME v1.2 shared task. Our approach assumes a multilingual perspective based on the recently introduced lateral inhibition layer and adversarial training to boost the performance of the employed multilingual language models. With the help of these two methods, we improve the F1-score of XLM-RoBERTa by approximately 2.7% on unseen multiword expressions, the main task of the PARSEME 1.2 edition. In addition, our results can be considered SOTA performance, as they outperform the previous results on Romanian obtained by the participants in this competition. © 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

    "Workshop Multiword Expressions, MWE - Proc."

  • ISBN

    978-195942959-3

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    7-13

  • Publisher name

    Association for Computational Linguistics

  • 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