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Designing a Prompt for Enhanced Text Summarization
Imagine you are tasked with using a Large Language Model to summarize a complex news article about a recent scientific discovery. You find that the model's initial summaries are often too simplistic and miss key nuances. Design a single, self-contained prompt that leverages the principle of learning from a flawed example to guide the model toward producing a more accurate and comprehensive summary. Your response should present the complete prompt you would use, including placeholders for the article and the flawed summary. Following the prompt, explain the reasoning behind each component of your design.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Creation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Simplified Deliberate-then-Generate Method for Deliberation Only
A user wants an AI model to translate the English sentence 'The early bird gets the worm' into formal Spanish. To improve the quality of the translation in a single attempt, the user provides the model with a flawed example. Which of the following prompts most effectively demonstrates the principle of learning from an incorrect example?
Improving LLM Code Generation with Prompting
Designing a Prompt for Enhanced Text Summarization