GPS: Genetic Prompt Search for Efficient Few-shot Learning

Understand

Prompt-based techniques have demostrated great potential for improving the few-shot generalization of pretrained language models.

• However, their performance heavily relies on the manual design of prompts and thus requires a lot of human efforts.
• In this paper, we introduce Genetic Prompt Search (GPS) to improve few-shot learning with prompts, which utilizes a genetic algorithm to automatically search for high-performing prompts.
• GPS is gradient-free and requires no update of model parameters but only a small validation set.