@inproceedings{parovic-etal-2024-investigating,
title = "Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer",
author = "Parovi{\'c}, Marinela and
Vuli{\'c}, Ivan and
Korhonen, Anna",
editor = "Graham, Yvette and
Purver, Matthew",
booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = mar,
year = "2024",
address = "St. Julian{'}s, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.eacl-short.12",
pages = "124--137",
abstract = "Cross-lingual transfer has recently been tackled through modular, parameter-efficient fine-tuning methods which allow arbitrary combinations of language and task modules for transfer of any task to any language. Concurrently, task arithmetic has emerged as a powerful and modular tool for editing pretrained models using multiple full fine-tunings. In this work, we connect the paradigms of task arithmetic and cross-lingual transfer, demonstrating that modularity for cross-lingual transfer can be achieved even with full model fine-tuning. Our approach displays strong performance on a range of multilingual benchmarks encompassing both high-resource and low-resource languages.",
}
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%0 Conference Proceedings
%T Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer
%A Parović, Marinela
%A Vulić, Ivan
%A Korhonen, Anna
%Y Graham, Yvette
%Y Purver, Matthew
%S Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F parovic-etal-2024-investigating
%X Cross-lingual transfer has recently been tackled through modular, parameter-efficient fine-tuning methods which allow arbitrary combinations of language and task modules for transfer of any task to any language. Concurrently, task arithmetic has emerged as a powerful and modular tool for editing pretrained models using multiple full fine-tunings. In this work, we connect the paradigms of task arithmetic and cross-lingual transfer, demonstrating that modularity for cross-lingual transfer can be achieved even with full model fine-tuning. Our approach displays strong performance on a range of multilingual benchmarks encompassing both high-resource and low-resource languages.
%U https://aclanthology.org/2024.eacl-short.12
%P 124-137
Markdown (Informal)
[Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer](https://aclanthology.org/2024.eacl-short.12) (Parović et al., EACL 2024)
ACL