How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets

Aarne Talman; Marianna Apidianaki; Stergios Chatzikyriakidis; Jörg Tiedemann

How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets

Aarne Talman, Marianna Apidianaki, Stergios Chatzikyriakidis, Jörg Tiedemann

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

Original language	English
Title of host publication	Proceedings of The 11th Joint Conference on Lexical and Computational Semantics
Editors	Vivi Nastase, Ellie Pavlick, Mohammad Taher Pilehvar, Jose Camacho-Collados, Alessandro Raganato
Number of pages	8
Place of Publication	Stroudsburg
Publisher	The Association for Computational Linguistics
Publication date	2022
Pages	226-233
ISBN (Electronic)	978-1-955917-98-8
Publication status	Published - 2022
MoE publication type	A4 Article in conference proceedings
Event	Joint Conference on Lexical and Computational Semantics - Seattle, United States Duration: 14 Jul 2022 → 15 Jul 2022 Conference number: 11

Fields of Science

6121 Languages
113 Computer and information sciences

Access to Document

2022.starsem-1.20Final published version, 238 KBLicence: CC BY

FoTran: Found in Translation - Natural Language Understanding with Cross-Lingual Grounding
Tiedemann, J. (Project manager), Attieh, J. (Participant), Aulamo, M. (Participant), Celikkanat, H. (Participant), De Gibert Bonet, O. (Participant), Grönroos, S.-A. (Participant), Mickus, T. (Participant), Raganato, A. (Participant), Scherrer, Y. (Participant), Silfverberg, M. (Participant), Sjöblom, E. I. (Participant), Talman, A. (Participant), Vazquez , R. (Participant), Virpioja, S. P. (Participant), Yli-Jyrä, A. (Participant), Zosa, E. (Participant), Celikkanat, H. (Participant), Raganato, A. (Participant), Silfverberg, M. (Participant), Sulubacak, U. (Participant) & Vazquez , R. (Participant)
01/09/2018 → 31/03/2024
Project: EU Horizon 2020: European Research Council: Consolidator Grant (H2020-ERC-COG)

Cite this

Talman, A., Apidianaki, M., Chatzikyriakidis, S., & Tiedemann, J. (2022). How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets. In V. Nastase, E. Pavlick, M. Taher Pilehvar, J. Camacho-Collados, & A. Raganato (Eds.), Proceedings of The 11th Joint Conference on Lexical and Computational Semantics (pp. 226-233). The Association for Computational Linguistics.

Talman, Aarne ; Apidianaki, Marianna ; Chatzikyriakidis, Stergios et al. / How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets. Proceedings of The 11th Joint Conference on Lexical and Computational Semantics. editor / Vivi Nastase ; Ellie Pavlick ; Mohammad Taher Pilehvar ; Jose Camacho-Collados ; Alessandro Raganato. Stroudsburg : The Association for Computational Linguistics, 2022. pp. 226-233

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title = "How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets",

keywords = "6121 Languages, 113 Computer and information sciences",

author = "Aarne Talman and Marianna Apidianaki and Stergios Chatzikyriakidis and J{\"o}rg Tiedemann",

year = "2022",

language = "English",

pages = "226--233",

editor = "Vivi Nastase and Ellie Pavlick and {Taher Pilehvar}, {Mohammad } and Camacho-Collados, {Jose } and Raganato, {Alessandro }",

booktitle = "Proceedings of The 11th Joint Conference on Lexical and Computational Semantics",

publisher = "The Association for Computational Linguistics",

address = "United States",

note = "Joint Conference on Lexical and Computational Semantics, SEM 2022 ; Conference date: 14-07-2022 Through 15-07-2022",

}

Talman, A, Apidianaki, M, Chatzikyriakidis, S & Tiedemann, J 2022, How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets. in V Nastase, E Pavlick, M Taher Pilehvar, J Camacho-Collados & A Raganato (eds), Proceedings of The 11th Joint Conference on Lexical and Computational Semantics. The Association for Computational Linguistics, Stroudsburg, pp. 226-233, Joint Conference on Lexical and Computational Semantics, Seattle, Washington, United States, 14/07/2022.

How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets. / Talman, Aarne; Apidianaki, Marianna; Chatzikyriakidis, Stergios et al.
Proceedings of The 11th Joint Conference on Lexical and Computational Semantics. ed. / Vivi Nastase; Ellie Pavlick; Mohammad Taher Pilehvar; Jose Camacho-Collados; Alessandro Raganato. Stroudsburg: The Association for Computational Linguistics, 2022. p. 226-233.

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

TY - GEN

T1 - How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets

AU - Talman, Aarne

AU - Apidianaki, Marianna

AU - Chatzikyriakidis, Stergios

AU - Tiedemann, Jörg

N1 - Conference code: 11

PY - 2022

Y1 - 2022

KW - 6121 Languages

KW - 113 Computer and information sciences

M3 - Conference contribution

SP - 226

EP - 233

BT - Proceedings of The 11th Joint Conference on Lexical and Computational Semantics

A2 - Nastase, Vivi

A2 - Pavlick, Ellie

A2 - Taher Pilehvar, Mohammad

A2 - Camacho-Collados, Jose

A2 - Raganato, Alessandro

PB - The Association for Computational Linguistics

CY - Stroudsburg

T2 - Joint Conference on Lexical and Computational Semantics

Y2 - 14 July 2022 through 15 July 2022

ER -

Talman A, Apidianaki M, Chatzikyriakidis S, Tiedemann J. How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets. In Nastase V, Pavlick E, Taher Pilehvar M, Camacho-Collados J, Raganato A, editors, Proceedings of The 11th Joint Conference on Lexical and Computational Semantics. Stroudsburg: The Association for Computational Linguistics. 2022. p. 226-233

How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets

Fields of Science

Access to Document

Projects

FoTran: Found in Translation - Natural Language Understanding with Cross-Lingual Grounding

Cite this