New Framework Enables Efficient Multilingual Code-Switching in Reasoning Models
Researchers propose a data-efficient method to train reasoning models to seamlessly switch between languages. This approach could revolutionize multilingual AI applications by leveraging code-switching as a strength rather than an error.