MoC generates K diverse concepts, then conditions hypothesis generation on each concept, yielding more semantically diverse LLM hypotheses and higher inductive-reasoning accuracy than IID sampling at equal K.
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Generating Diverse Hypotheses for Inductive Reasoning
MoC generates K diverse concepts, then conditions hypothesis generation on each concept, yielding more semantically diverse LLM hypotheses and higher inductive-reasoning accuracy than IID sampling at equal K.