AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought
Researchers introduce AdaMCoT, a framework that improves multilingual reasoning in large language models by dynamically routing intermediate thoughts through optimal 'thinking languages' before generating target-language responses. The approach achieves significant performance gains in low-resource languages without requiring additional pretraining, addressing a key limitation in current multilingual AI systems.