Does typological blinding impede cross-lingual sharing?

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

Standard

Does typological blinding impede cross-lingual sharing? / Bjerva, Johannes; Augenstein, Isabelle.

EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, 2021. p. 480-486.

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

Harvard

Bjerva, J & Augenstein, I 2021, Does typological blinding impede cross-lingual sharing? in EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, pp. 480-486, 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021, Virtual, Online, 19/04/2021. https://doi.org/10.18653/v1/2021.eacl-main.38

APA

Bjerva, J., & Augenstein, I. (2021). Does typological blinding impede cross-lingual sharing? In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference (pp. 480-486). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eacl-main.38

Vancouver

Bjerva J, Augenstein I. Does typological blinding impede cross-lingual sharing? In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics. 2021. p. 480-486 https://doi.org/10.18653/v1/2021.eacl-main.38

Author

Bjerva, Johannes ; Augenstein, Isabelle. / Does typological blinding impede cross-lingual sharing?. EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, 2021. pp. 480-486

Bibtex

@inproceedings{956b99748b95402c8bea65c2cc790a4d,
title = "Does typological blinding impede cross-lingual sharing?",
abstract = "Bridging the performance gap between high- and low-resource languages has been the focus of much previous work. Typological features from databases such as the World Atlas of Language Structures (WALS) are a prime candidate for this, as such data exists even for very low-resource languages. However, previous work has only found minor benefits from using typological information. Our hypothesis is that a model trained in a cross-lingual setting will pick up on typological cues from the input data, thus overshadowing the utility of explicitly using such features. We verify this hypothesis by blinding a model to typological information, and investigate how cross-lingual sharing and performance is impacted. Our model is based on a cross-lingual architecture in which the latent weights governing the sharing between languages is learnt during training. We show that (i) preventing this model from exploiting typology severely reduces performance, while a control experiment reaffirms that (ii) encouraging sharing according to typology somewhat improves performance.",
author = "Johannes Bjerva and Isabelle Augenstein",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics; 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 ; Conference date: 19-04-2021 Through 23-04-2021",
year = "2021",
doi = "10.18653/v1/2021.eacl-main.38",
language = "English",
pages = "480--486",
booktitle = "EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference",
publisher = "Association for Computational Linguistics",

}

RIS

TY - GEN

T1 - Does typological blinding impede cross-lingual sharing?

AU - Bjerva, Johannes

AU - Augenstein, Isabelle

N1 - Publisher Copyright: © 2021 Association for Computational Linguistics

PY - 2021

Y1 - 2021

N2 - Bridging the performance gap between high- and low-resource languages has been the focus of much previous work. Typological features from databases such as the World Atlas of Language Structures (WALS) are a prime candidate for this, as such data exists even for very low-resource languages. However, previous work has only found minor benefits from using typological information. Our hypothesis is that a model trained in a cross-lingual setting will pick up on typological cues from the input data, thus overshadowing the utility of explicitly using such features. We verify this hypothesis by blinding a model to typological information, and investigate how cross-lingual sharing and performance is impacted. Our model is based on a cross-lingual architecture in which the latent weights governing the sharing between languages is learnt during training. We show that (i) preventing this model from exploiting typology severely reduces performance, while a control experiment reaffirms that (ii) encouraging sharing according to typology somewhat improves performance.

AB - Bridging the performance gap between high- and low-resource languages has been the focus of much previous work. Typological features from databases such as the World Atlas of Language Structures (WALS) are a prime candidate for this, as such data exists even for very low-resource languages. However, previous work has only found minor benefits from using typological information. Our hypothesis is that a model trained in a cross-lingual setting will pick up on typological cues from the input data, thus overshadowing the utility of explicitly using such features. We verify this hypothesis by blinding a model to typological information, and investigate how cross-lingual sharing and performance is impacted. Our model is based on a cross-lingual architecture in which the latent weights governing the sharing between languages is learnt during training. We show that (i) preventing this model from exploiting typology severely reduces performance, while a control experiment reaffirms that (ii) encouraging sharing according to typology somewhat improves performance.

U2 - 10.18653/v1/2021.eacl-main.38

DO - 10.18653/v1/2021.eacl-main.38

M3 - Article in proceedings

AN - SCOPUS:85107280548

SP - 480

EP - 486

BT - EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

PB - Association for Computational Linguistics

T2 - 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021

Y2 - 19 April 2021 through 23 April 2021

ER -

ID: 283135291