Can Multilingual Transformers Fight the COVID-19 Infodemic?

Lasitha Uyangodage; Tharindu Ranasinghe; Hansi Hettiarachchi

doi:10.26615/978-954-452-072-4_160

Can Multilingual Transformers Fight the COVID-19 Infodemic?

Lasitha Uyangodage^*
, Tharindu Ranasinghe
, Hansi Hettiarachchi

^*Corresponding author for this work

University of Münster
University of Wolverhampton

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (SciVal)

Original language	English
Title of host publication	International Conference Recent Advances in Natural Language Processing, RANLP 2021
Subtitle of host publication	Deep Learning for Natural Language Processing Methods and Applications - Proceedings
Editors	Galia Angelova, Maria Kunilovskaya, Ruslan Mitkov, Ivelina Nikolova-Koleva
Publisher	Incoma Ltd
Pages	1432-1437
Number of pages	6
ISBN (Electronic)	9789544520724
DOIs	https://doi.org/10.26615/978-954-452-072-4_160
Publication status	Published (VoR) - 2021
Event	International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021 - Virtual, Online Duration: 1 Sept 2021 → 3 Sept 2021

Publication series

Name	International Conference Recent Advances in Natural Language Processing, RANLP
ISSN (Print)	1313-8502

Conference

Conference	International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021
City	Virtual, Online
Period	1/09/21 → 3/09/21

Access to Document

10.26615/978-954-452-072-4_160

Cite this

Uyangodage, L., Ranasinghe, T., & Hettiarachchi, H. (2021). Can Multilingual Transformers Fight the COVID-19 Infodemic? In G. Angelova, M. Kunilovskaya, R. Mitkov, & I. Nikolova-Koleva (Eds.), International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings (pp. 1432-1437). (International Conference Recent Advances in Natural Language Processing, RANLP). Incoma Ltd. https://doi.org/10.26615/978-954-452-072-4_160

Uyangodage, Lasitha ; Ranasinghe, Tharindu ; Hettiarachchi, Hansi. / Can Multilingual Transformers Fight the COVID-19 Infodemic?. International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. editor / Galia Angelova ; Maria Kunilovskaya ; Ruslan Mitkov ; Ivelina Nikolova-Koleva. Incoma Ltd, 2021. pp. 1432-1437 (International Conference Recent Advances in Natural Language Processing, RANLP).

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title = "Can Multilingual Transformers Fight the COVID-19 Infodemic?",

author = "Lasitha Uyangodage and Tharindu Ranasinghe and Hansi Hettiarachchi",

note = "Publisher Copyright: {\textcopyright} 2021 Incoma Ltd. All rights reserved.; International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021 ; Conference date: 01-09-2021 Through 03-09-2021",

year = "2021",

doi = "10.26615/978-954-452-072-4\_160",

language = "English",

series = "International Conference Recent Advances in Natural Language Processing, RANLP",

publisher = "Incoma Ltd",

pages = "1432--1437",

editor = "Galia Angelova and Maria Kunilovskaya and Ruslan Mitkov and Ivelina Nikolova-Koleva",

booktitle = "International Conference Recent Advances in Natural Language Processing, RANLP 2021",

}

Uyangodage, L, Ranasinghe, T & Hettiarachchi, H 2021, Can Multilingual Transformers Fight the COVID-19 Infodemic? in G Angelova, M Kunilovskaya, R Mitkov & I Nikolova-Koleva (eds), International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. International Conference Recent Advances in Natural Language Processing, RANLP, Incoma Ltd, pp. 1432-1437, International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021, Virtual, Online, 1/09/21. https://doi.org/10.26615/978-954-452-072-4_160

Can Multilingual Transformers Fight the COVID-19 Infodemic? / Uyangodage, Lasitha; Ranasinghe, Tharindu; Hettiarachchi, Hansi.
International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. ed. / Galia Angelova; Maria Kunilovskaya; Ruslan Mitkov; Ivelina Nikolova-Koleva. Incoma Ltd, 2021. p. 1432-1437 (International Conference Recent Advances in Natural Language Processing, RANLP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review