A survey that unifies prior code-switching research for LLMs into a taxonomy of data, modeling, and evaluation and distills it into actionable recommendations for practitioners.
Mech- anistic understanding and mitigation of language confu- sion in english-centric large language models.ArXiv, abs/2505.16538,
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Code Mixologist : A Practitioner's Guide to Building Code-Mixed LLMs
A survey that unifies prior code-switching research for LLMs into a taxonomy of data, modeling, and evaluation and distills it into actionable recommendations for practitioners.