Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models. (arXiv:2208.07852v1 [cs.CL])

State-of-the-art neural language models can now be used to solve ad-hoc
language tasks through zero-shot prompting without the need for supervised
training. This approach has gained popularity in recent years, and researchers
have demonstrated prompts that achieve strong accuracy on specific NLP tasks.
However, finding a prompt for new tasks requires experimentation. Different
prompt templates with different wording choices lead to significant accuracy
differences. PromptIDE allows users to experiment with prompt variations,
visualize prompt performance, and iteratively optimize prompts. We …

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