Optimal Self-Consistency for Efficient Reasoning with Large Language Models

arXiv:2511.12309v2 Announce Type: replace Abstract: Self-consistency (SC) is a widely used test-time inference technique for improving performance in chain-of-thought reasoning. It consists of generating multiple responses, or ``samples", from a large language model (LLM) and selecting the most frequent answer. This procedure can naturally be viewed as a majority vote or empirical mode estimation. Despite its effectiveness, self-consistency is prohibitively expensive at scale when naively applied to datasets, and it lacks a unified theoretical understanding of sample efficiency and scaling beh

Source: arXiv cs.LG — read the full report at the original publisher.

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