Papers with Genetic Prompt Search

1 papers
GPS: Genetic Prompt Search for Efficient Few-Shot Learning (2022.emnlp-main)

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Challenge: Pretrained language models are often finetuned for downstream tasks, which has been shown to improve performance over non-pretrained models.
Approach: They propose a genetic algorithm to automatically search for the best prompt for few-shot learning with pretrained language models by gradient-free algorithm.
Outcome: Experiments on diverse datasets show that the proposed method outperforms manual prompts by 2.6 points.

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