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Improving Prompt Structure for Better LLM Outputs
A user is trying to get a large language model to summarize news articles. They are using the prompt below but find that the model sometimes provides a very long summary, sometimes just a single sentence, and occasionally adds its own opinions. Based on your understanding of prompt components, analyze the user's prompt and explain which specific components are missing or poorly defined, and how improving them would lead to more consistent and accurate summaries.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Example of a Complete Prompt for Polarity Classification
A user provides the following text to a large language model:
`Classify the sentiment of the following movie review. The sentiment can be one of {positive, negative}.
Review: "This film was a masterpiece of storytelling and cinematography." Sentiment:`
Which of the following options correctly breaks down the components of this prompt and their respective functions?
Analyzing a Flawed Prompt
Improving Prompt Structure for Better LLM Outputs