🟢 Introduction to Ensembling Prompting

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Last updated on September 27, 2024

Welcome to the ensembling section of the advanced Prompt Engineering Guide.

Ensembling is based on using multiple prompts to tackle the problem and then aggregating these responses into a final output.

Stay tuned for ensembling techniques!

Valeriia Kuka

Valeriia Kuka, Head of Content at Learn Prompting, is passionate about making AI and ML accessible. Valeriia previously grew a 60K+ follower AI-focused social media account, earning reposts from Stanford NLP, Amazon Research, Hugging Face, and AI researchers. She has also worked with AI/ML newsletters and global communities with 100K+ members and authored clear and concise explainers and historical articles.

🟢 Introduction to Ensembling Prompting

Valeriia Kuka

🟦 Consistency-based Self-adaptive Prompting (COSP)

🟦 DiVeRSe (Diverse Verifier on Reasoning Step)

🟦 Max Mutual Information (MMI) Method

🟦 Mixture of Reasoning Experts (MoRE)

🟦 Prompt Paraphrasing

🟢 Universal Self-Consistency

🟦 Step-Back Prompting

🟦 Mixture of Reasoning Experts (MoRE)

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