AI RESEARCH

Learning to Think from Multiple Thinkers

arXiv CS.LG

ArXi:2604.24737v1 Announce Type: new We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e.g., step-by-step solutions to math problems We consider classes that are computationally easy to learn using CoT supervision from a single thinker, but hard to learn with only end-result supervision, i.e., without CoT (Joshi 2025