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A team is developing a system to generate instructional data. They begin with a fixed set of 500 human-written tasks. A language model is then prompted using only these 500 tasks to generate thousands of new examples. The newly generated instructions are collected for the final dataset but are never added back to the original pool of 500 tasks. What is the most significant limitation of this approach?
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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
Evaluation in Bloom's Taxonomy
Cognitive Psychology
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Structure of a Task Sample in Self-Instruct
An engineer is implementing a process to generate training data. The process begins with 100 manually-created instructional prompts. In each cycle, the system uses a language model to generate 20 new prompts, which are then reviewed for quality and added to the existing set. Which statement best analyzes the state of the prompt collection after 10 successful cycles?
A team is developing a system to generate instructional data. They begin with a fixed set of 500 human-written tasks. A language model is then prompted using only these 500 tasks to generate thousands of new examples. The newly generated instructions are collected for the final dataset but are never added back to the original pool of 500 tasks. What is the most significant limitation of this approach?
A team is using an automated process to expand a collection of instructional tasks, starting from a small set of human-written examples. Arrange the following events to show the correct sequence for how a single new, high-quality task is generated and integrated into the collection.