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PromptWizard is a discrete prompt optimization framework that employs a self-evolving mechanism where the LLM generates, critiques, and refines its own prompts and examples, continuously improving through iterative feedback and synthesis. This self-adaptive approach ensures holistic optimization by evolving both the instructions and in-context learning examples for better task performance.
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Three key components of PromptWizard are te following :
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Three key components of PromptWizard are the following :
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- Feedback-driven Refinement: LLM generates, critiques, and refines its own prompts and examples, continuously improving through iterative feedback and synthesis
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- Critique and Synthesize diverse examples: Generates synthetic examples that are robust, diverse and task-aware. Also it optimizes both prompt and examples in tandem
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