[Review] Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm

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The paper discusses about prompt engineering, mainly focusing on GPT-3. It compiles some prompt engineering approaches.

Background:

The recent rise of massive self-supervised language models such as GPT-3 arises the interests of prompt engineering. For such models, 0-shot prompts may significantly outperform few-shot prompts. So, the importance of prompt engineering is again being promoted.

Some facts:

• 0-shot may outperform few-shot: instead of treating examples as a categorical guide, it is inferred that their semantic meaning is relevant to the task.
• For GPT-3, its resemblance not to a single human author but a superposition of authors.