@inproceedings{choudhary-2021-improving,
title = "Improving the Performance of {UD}ify with Linguistic Typology Knowledge",
author = "Choudhary, Chinmay",
editor = {Vylomova, Ekaterina and
Salesky, Elizabeth and
Mielke, Sabrina and
Lapesa, Gabriella and
Kumar, Ritesh and
Hammarstr{\"o}m, Harald and
Vuli{\'c}, Ivan and
Korhonen, Anna and
Reichart, Roi and
Ponti, Edoardo Maria and
Cotterell, Ryan},
booktitle = "Proceedings of the Third Workshop on Computational Typology and Multilingual NLP",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.sigtyp-1.5",
doi = "10.18653/v1/2021.sigtyp-1.5",
pages = "38--60",
abstract = "UDify is the state-of-the-art language-agnostic dependency parser which is trained on a polyglot corpus of 75 languages. This multilingual modeling enables the model to generalize over unknown/lesser-known languages, thus leading to improved performance on low-resource languages. In this work we used linguistic typology knowledge available in URIEL database, to improve the cross-lingual transferring ability of UDify even further.",
}
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%0 Conference Proceedings
%T Improving the Performance of UDify with Linguistic Typology Knowledge
%A Choudhary, Chinmay
%Y Vylomova, Ekaterina
%Y Salesky, Elizabeth
%Y Mielke, Sabrina
%Y Lapesa, Gabriella
%Y Kumar, Ritesh
%Y Hammarström, Harald
%Y Vulić, Ivan
%Y Korhonen, Anna
%Y Reichart, Roi
%Y Ponti, Edoardo Maria
%Y Cotterell, Ryan
%S Proceedings of the Third Workshop on Computational Typology and Multilingual NLP
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F choudhary-2021-improving
%X UDify is the state-of-the-art language-agnostic dependency parser which is trained on a polyglot corpus of 75 languages. This multilingual modeling enables the model to generalize over unknown/lesser-known languages, thus leading to improved performance on low-resource languages. In this work we used linguistic typology knowledge available in URIEL database, to improve the cross-lingual transferring ability of UDify even further.
%R 10.18653/v1/2021.sigtyp-1.5
%U https://aclanthology.org/2021.sigtyp-1.5
%U https://doi.org/10.18653/v1/2021.sigtyp-1.5
%P 38-60
Markdown (Informal)
[Improving the Performance of UDify with Linguistic Typology Knowledge](https://aclanthology.org/2021.sigtyp-1.5) (Choudhary, SIGTYP 2021)
ACL