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Methods for Creating Diverse Prompts
To achieve varied outputs in prompt ensembling, it is crucial to construct high-quality, diverse prompts, often by incorporating different demonstration examples. Common methods include manually creating unique demonstrations for each prompt, using Large Language Models (LLMs) to automatically generate demonstrations and prompts, rearranging the order of demonstrations, prompting LLMs to generate similar prompt variations, or transforming prompts into other formats, such as translating them into different languages. These techniques are often combined in practice to maximize diversity.
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Foundations of Large Language Models
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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