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An AI development team is using a large language model to automatically generate a dataset of programming problems and their solutions. They start with a simple instruction-generation prompt like: Generate a new programming problem. After generating 10,000 examples, they find that the problems are repetitive (e.g., mostly sorting lists) and the generated solutions are often suboptimal. Which of the following modifications to their process would be the most effective first step to improve both the diversity of the problems and the quality of the solutions?
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Ch.4 Alignment - 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
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Empirical Science
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An AI development team is using a large language model to automatically generate a dataset of programming problems and their solutions. They start with a simple instruction-generation prompt like:
Generate a new programming problem.After generating 10,000 examples, they find that the problems are repetitive (e.g., mostly sorting lists) and the generated solutions are often suboptimal. Which of the following modifications to their process would be the most effective first step to improve both the diversity of the problems and the quality of the solutions?