Beyond Bilingual Transfer: Multilingual Code-Switching in Instruction Tuning
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Computer Science > Computation and Language
Title:Beyond Bilingual Transfer: Multilingual Code-Switching in Instruction Tuning
Abstract:Recent studies have shown that code-switching data (CSD), in which multiple languages are mixed within the same context, can improve cross-lingual transfer and multilingual alignment in large language models (LLMs). However, existing studies primarily focus on bilingual transfer between English and a target language, leaving multilingual settings involving three or more languages largely unexplored. In this work, we investigate multilingual code-switching instruction tuning across four languages: English, Japanese, Korean, and Chinese. We evaluate multilingual understanding on Belebele. Our experiments show that simple sentence-level multilingual CSD consistently improves average multilingual performance across all four languages, indicating that multilingual code-switching can be effective beyond bilingual transfer settings.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2605.29414 [cs.CL] |
| (or arXiv:2605.29414v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.29414
arXiv-issued DOI via DataCite (pending registration)
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