This paper presents CS-CoT, a novel framework for code-switched reasoning in multilingual contexts. It introduces three innovations: Language-Aware Continuous Routing, Cross-Lingual Thought Alignment, and Adaptive Switch Point Detection, achieving 15.3% higher accuracy than explicit CoT baselines.
Key findings
CS-CoT operates in a language-agnostic continuous space for seamless reasoning across languages.
The framework introduces Language-Aware Continuous Routing, Cross-Lingual Thought Alignment, and Adaptive Switch Point Detection.
CS-CoT achieves 15.3% higher accuracy on code-switched reasoning tasks compared to explicit CoT baselines.
Token generation is reduced by 28%, and cross-lingual alignment losses decrease by 42%.
Limitations & open questions
The framework's performance in extremely low-resource language pairs is not yet evaluated.
The scalability of CS-CoT in real-world applications with a large number of languages remains to be seen.