Approaching SMM4H with auto-regressive language models and back-translation

Joseph Cornelius; Tilia Ellendorff; Fabio Rinaldi

doi:10.18653/v1/2021.smm4h-1.32

Approaching SMM4H with auto-regressive language models and back-translation

Joseph Cornelius, Tilia Ellendorff, Fabio Rinaldi

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Abstract

We describe our submissions to the 6th edition of the Social Media Mining for Health Applications (SMM4H) shared task. Our team (OGNLP) participated in the sub-task: Classification of tweets self-reporting potential cases of COVID-19 (Task 5). For our submissions, we employed systems based on auto-regressive transformer models (XLNet) and back-translation for balancing the dataset.

Anthology ID:: 2021.smm4h-1.32
Volume:: Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
Month:: June
Year:: 2021
Address:: Mexico City, Mexico
Editors:: Arjun Magge, Ari Klein, Antonio Miranda-Escalada, Mohammed Ali Al-garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulalia Farre-Maduell, Salvador Lima Lopez, Ivan Flores, Karen O'Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan M Banda, Martin Krallinger, Graciela Gonzalez-Hernandez
Venue:: SMM4H
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 146–148
Language:
URL:: https://aclanthology.org/2021.smm4h-1.32/
DOI:: 10.18653/v1/2021.smm4h-1.32
Bibkey:
Cite (ACL):: Joseph Cornelius, Tilia Ellendorff, and Fabio Rinaldi. 2021. Approaching SMM4H with auto-regressive language models and back-translation. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 146–148, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):: Approaching SMM4H with auto-regressive language models and back-translation (Cornelius et al., SMM4H 2021)
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PDF:: https://aclanthology.org/2021.smm4h-1.32.pdf

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@inproceedings{cornelius-etal-2021-approaching,
    title = "Approaching {SMM}4{H} with auto-regressive language models and back-translation",
    author = "Cornelius, Joseph  and
      Ellendorff, Tilia  and
      Rinaldi, Fabio",
    editor = "Magge, Arjun  and
      Klein, Ari  and
      Miranda-Escalada, Antonio  and
      Al-garadi, Mohammed Ali  and
      Alimova, Ilseyar  and
      Miftahutdinov, Zulfat  and
      Farre-Maduell, Eulalia  and
      Lopez, Salvador Lima  and
      Flores, Ivan  and
      O'Connor, Karen  and
      Weissenbacher, Davy  and
      Tutubalina, Elena  and
      Sarker, Abeed  and
      Banda, Juan M  and
      Krallinger, Martin  and
      Gonzalez-Hernandez, Graciela",
    booktitle = "Proceedings of the Sixth Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
    month = jun,
    year = "2021",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.smm4h-1.32/",
    doi = "10.18653/v1/2021.smm4h-1.32",
    pages = "146--148",
    abstract = "We describe our submissions to the 6th edition of the Social Media Mining for Health Applications (SMM4H) shared task. Our team (OGNLP) participated in the sub-task: Classification of tweets self-reporting potential cases of COVID-19 (Task 5). For our submissions, we employed systems based on auto-regressive transformer models (XLNet) and back-translation for balancing the dataset."
}

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%0 Conference Proceedings
%T Approaching SMM4H with auto-regressive language models and back-translation
%A Cornelius, Joseph
%A Ellendorff, Tilia
%A Rinaldi, Fabio
%Y Magge, Arjun
%Y Klein, Ari
%Y Miranda-Escalada, Antonio
%Y Al-garadi, Mohammed Ali
%Y Alimova, Ilseyar
%Y Miftahutdinov, Zulfat
%Y Farre-Maduell, Eulalia
%Y Lopez, Salvador Lima
%Y Flores, Ivan
%Y O’Connor, Karen
%Y Weissenbacher, Davy
%Y Tutubalina, Elena
%Y Sarker, Abeed
%Y Banda, Juan M.
%Y Krallinger, Martin
%Y Gonzalez-Hernandez, Graciela
%S Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
%D 2021
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F cornelius-etal-2021-approaching
%X We describe our submissions to the 6th edition of the Social Media Mining for Health Applications (SMM4H) shared task. Our team (OGNLP) participated in the sub-task: Classification of tweets self-reporting potential cases of COVID-19 (Task 5). For our submissions, we employed systems based on auto-regressive transformer models (XLNet) and back-translation for balancing the dataset.
%R 10.18653/v1/2021.smm4h-1.32
%U https://aclanthology.org/2021.smm4h-1.32/
%U https://doi.org/10.18653/v1/2021.smm4h-1.32
%P 146-148

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Markdown (Informal)

[Approaching SMM4H with auto-regressive language models and back-translation](https://aclanthology.org/2021.smm4h-1.32/) (Cornelius et al., SMM4H 2021)

Approaching SMM4H with auto-regressive language models and back-translation (Cornelius et al., SMM4H 2021)

ACL

Joseph Cornelius, Tilia Ellendorff, and Fabio Rinaldi. 2021. Approaching SMM4H with auto-regressive language models and back-translation. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 146–148, Mexico City, Mexico. Association for Computational Linguistics.