Few-Shot Prompt Perturbations and Reasoning Accuracy in Large Language Models

This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What is the impact of few-shot prompt perturbations on the reasoning accuracy of large language models across mathematical and logical deduction benchmarks. 10 claims were extracted from source literature; 10 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 9.3/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: What is the impact of few-shot prompt perturbations on the reasoning accuracy of large language models across mathematical and logical deduction benchmarks?

Autonomous literature synthesis. Automated review score: 9.3/10. Full text and citation available at Assignee Research.