AI RESEARCH
Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning
arXiv CS.LG
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ArXi:2604.17433v1 Announce Type: cross Self-consistency (SC) is a popular technique for improving the reasoning accuracy of large language models by aggregating multiple sampled outputs, but it comes at a high computational cost due to extensive sampling. We