Ensemble Methods

7 frameworks — Combine multiple reasoning paths, prompts, or outputs to achieve more reliable and accurate results.

Overview

Ensemble methods combine multiple reasoning paths, prompts, or outputs to achieve more reliable and accurate results. By generating diverse solutions and selecting the best, these techniques reduce the impact of any single error or bias.

Use ensemble methods when reliability is critical — when a wrong answer is worse than a slower process. They are ideal for automated pipelines, evaluation tasks, and any scenario where you can trade computation time for accuracy.

Technique Comparison

Side-by-side comparison of all 12 techniques in this category.

Technique Year Best For Key Strength Complexity
Self-Consistency 2022 Reliable answers Majority voting Medium
COSP 2023 Zero-shot tasks Self-generated demos Medium
Dense Prompting 2024 Multi-perspective Perspective fusion Medium
Max Mutual Information 2024 Prompt selection Information theory High
Meta-Reasoning 2024 Process selection Reasoning evaluation High
Universal Self-Consistency 2023 Free-form text Text consistency Medium
DiVeRSe 2022 Step verification Diverse verifier High
Recommended Starting Point

Try Self-Consistency

Self-Consistency is the simplest ensemble method — ask the same question multiple ways, then take the majority vote. It dramatically improves accuracy with minimal extra effort.