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Diagnosing Low Diversity in a Generated Dataset
Based on the process described in the case study, what is the most probable weakness in the generation process causing the lack of diversity, and what specific change would best address this issue?
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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
Social Science
Empirical Science
Science
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Diagnosing Low Diversity in a Generated Dataset
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Biased Predictions in LLM-based Synthetic Data Generation
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?