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@inproceedings{1847597,
author = {Štefánik, Michal and Novotný, Vít and Groverová, Nikola and Sojka, Petr},
address = {Dublin, Irsko},
booktitle = {Proceedings of the 60th Conference of Association of Computational Linguistics, ACL 2022},
doi = {http://dx.doi.org/10.18653/v1/2022.acl-demo.26},
editor = {Valerio Basile, Zornitsa Kozareva, Sanja Stajner},
keywords = {Adaptor library; domain adaptation; similarity search; vector space; embeddings},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Dublin, Irsko},
isbn = {978-1-955917-24-7},
pages = {261-269},
publisher = {Association for Computational Linguistics, ACL},
title = {AdaptOr: Objective-Centric Adaptation Framework for Language Models},
url = {https://arxiv.org/abs/2203.03989},
year = {2022}
}
TY - JOUR
ID - 1847597
AU - Štefánik, Michal - Novotný, Vít - Groverová, Nikola - Sojka, Petr
PY - 2022
TI - AdaptOr: Objective-Centric Adaptation Framework for Language Models
PB - Association for Computational Linguistics, ACL
CY - Dublin, Irsko
SN - 9781955917247
KW - Adaptor library
KW - domain adaptation
KW - similarity search
KW - vector space
KW - embeddings
UR - https://arxiv.org/abs/2203.03989
N2 - Progress in natural language processing research is catalyzed by the possibilities given by the widespread software frameworks. This paper introduces the Adaptor library that transposes the traditional model-centric approach composed of pre-training + fine-tuning steps to the objective-centric approach, composing the training process by applications of selected objectives. We survey research directions that can benefit from enhanced objective-centric experimentation in multitask training, custom objectives development, dynamic training curricula, or domain adaptation. Adaptor aims to ease the reproducibility of these research directions in practice. Finally, we demonstrate the practical applicability of Adaptor in selected unsupervised domain adaptation scenarios.
ER -
ŠTEFÁNIK, Michal, Vít NOVOTNÝ, Nikola GROVEROVÁ a Petr SOJKA. AdaptOr: Objective-Centric Adaptation Framework for Language Models. In Valerio Basile, Zornitsa Kozareva, Sanja Stajner. \textit{Proceedings of the 60th Conference of Association of Computational Linguistics, ACL 2022}. Dublin, Irsko: Association for Computational Linguistics, ACL. s.~261-269. ISBN~978-1-955917-24-7. doi:10.18653/v1/2022.acl-demo.26. 2022.
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