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Article summary:

1. Self-Refine is a novel iterative refinement approach that uses self-feedback to improve natural language processing models.

2. The approach involves generating multiple candidate outputs and using a self-feedback mechanism to select the best one for further refinement.

3. Self-Refine outperforms existing state-of-the-art methods on several benchmark datasets, demonstrating its effectiveness in improving model performance.

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