Reliability-Aware Adaptive Self-Consistency for Efficient Sampling in LLM Reasoning

• URL: http://arxiv.org/abs/2601.02970v1
• Date: Tue, 06 Jan 2026 12:27:53 GMT
• Title: Reliability-Aware Adaptive Self-Consistency for Efficient Sampling in LLM Reasoning
• Abstract summary: Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost.<n>We propose Reliability-Aware Adaptive Self-Consistency (ReASC), which addresses this limitation by reframing adaptive sampling from response counting to evidence sufficiency.<n>ReASC consistently achieves the best accuracy-cost trade-off compared to existing baselines, yielding improved inference efficiency across model scales from 3B to 27B parameters.
• Score: 20.371912257758634
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost. Adaptive self-consistency methods mitigate this issue by adjusting the sampling budget; however, they rely on count-based stopping rules that treat all responses equally, often leading to unnecessary sampling. We propose Reliability-Aware Adaptive Self-Consistency (ReASC), which addresses this limitation by reframing adaptive sampling from response counting to evidence sufficiency, leveraging response-level confidence for principled information aggregation. ReASC operates in two stages: a single-sample decision stage that resolves instances confidently answerable from a single response, and a reliability-aware accumulation stage that aggregates responses by jointly leveraging their frequency and confidence. Across five models and four datasets, ReASC consistently achieves the best accuracy-cost trade-off compared to existing baselines, yielding improved inference efficiency across model scales from 3B to 27B parameters. As a concrete example, ReASC reduces inference cost by up to 70\% relative to self-consistency while preserving accuracy on GSM8K using Gemma-3-4B-it.

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