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AI at NETC: Zero-Shot Prompting

A guide for Faculty and Students about using AI.

Emotion Prompting

Leverages emotional language to improve LLM accuracy and response quality by tapping into emotion-rich training data.

To use emotion prompting, you can add any of these phrases to your original prompt:

  • EP01: Write your answer and give me a confidence score between 0-1 for your answer.
  • EP02: This is very important to my career.
  • EP03: You'd better be sure.
  • EP04: Are you sure?
  • EP05: Are you sure that's your final answer? It might be worth taking another look.
  • EP07: Are you sure that's your final answer? Believe in your abilities and strive for excellence. Your hard work will yield remarkable results.
  • EP08: Embrace challenges as opportunities for growth. Each obstacle you overcome brings you closer to success.
  • EP09: Stay focused and dedicated to your goals. Your consistent efforts will lead to outstanding achievements.
  • EP10: Take pride in your work and give it your best. Your commitment to excellence sets you apart.
  • EP11: Remember that progress is made one step at a time. Stay determined and keep moving forward.

Role Prompting

Assigns roles to the LLM, creating more context-specific relevant responses for various tasks. By including in your prompt for the LLM a statement for them to take on the persona or role of a particular occupation or even person, you can alter the output in a way that may be more useful to your needs for the output.

Example:

You are a historian. Explain the significance of the industrial revolution.
You are a salesman. Write a quick outreach email to [person] about partnering up.

 

Rephrase and Response (RaR)

Asks the model to rephrase the prompt before answering, reducing ambiguity and improving clarity.

Apart from adding "Rephrase and expand the question, and respond" to the prompt, you can use many other variations for asking a model to rephrase the question:

  • Reword and elaborate on the inquiry, then provide an answer.
  • Reframe the question with additional context and detail, then provide an answer.
  • Modify the original question for clarity and detail, then offer an answer.
  • Restate and elaborate on the inquiry before proceeding with a response.

All models can benefit from rephrasing questions, with more advanced models expected to gain a larger improvement.