Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer

Marinela Parović, Ivan Vulić, Anna Korhonen


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.
Anthology ID:
2024.eacl-short.12
Volume:
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Yvette Graham, Matthew Purver
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
124–137
Language:
URL:
https://aclanthology.org/2024.eacl-short.12
DOI:
Bibkey:
Cite (ACL):
Marinela Parović, Ivan Vulić, and Anna Korhonen. 2024. Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers), pages 124–137, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
Investigating the Potential of Task Arithmetic for Cross-Lingual Transfer (Parović et al., EACL 2024)
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PDF:
https://aclanthology.org/2024.eacl-short.12.pdf