Minimal Pair-Based Evaluation of Code-Switching

Igor Sterner, Simone Teufel


Abstract
There is a lack of an evaluation methodology that estimates the extent to which large language models (LLMs) use code-switching (CS) in the same way as bilinguals. Existing methods do not have wide language coverage, fail to account for the diverse range of CS phenomena, or do not scale. We propose an intervention based on minimal pairs of CS. Each minimal pair contains one naturally occurring CS sentence and one minimally manipulated variant. We collect up to 1,000 such pairs each for 11 language pairs. Our human experiments show that, for every language pair, bilinguals consistently prefer the naturally occurring CS sentence. Meanwhile our experiments with current LLMs show that the larger the model, the more consistently it assigns higher probability to the naturally occurring CS sentence than to the variant. In accordance with theoretical claims, the largest probability differences arise in those pairs where the manipulated material consisted of closed-class words.
Anthology ID:
2025.acl-long.910
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
18575–18598
Language:
URL:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.910/
DOI:
Bibkey:
Cite (ACL):
Igor Sterner and Simone Teufel. 2025. Minimal Pair-Based Evaluation of Code-Switching. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 18575–18598, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Minimal Pair-Based Evaluation of Code-Switching (Sterner & Teufel, ACL 2025)
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PDF:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.910.pdf