Prompt Ensembling
Prompt ensembling is a technique that runs multiple variations of a prompt for the same task and combines their outputs to produce a more accurate and robust final result. By varying the wording, structure, or perspective across prompts, ensembling reduces the impact of any single prompt's weaknesses and captures a more complete range of the model's knowledge.
Example
To classify whether a product review is positive or negative, you run three prompt variants: one asks "Is this review positive or negative?", another says "Rate the sentiment of this text," and a third uses "Would the reviewer recommend this product?" You take the majority vote across all three responses for a more reliable classification.
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