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Predicting Model Behavior from a Few-Shot Pattern
A developer is using a large language model to extract company names from news headlines. They provide the following series of demonstrations in a prompt. Based on the established input-output pattern, what is the most likely output the model will generate for the final headline? Explain your reasoning.
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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
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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Use of Simpler Patterns in Few-Shot Learning
A user provides a language model with the following examples to teach it a new task:
Input: Apple -> Output: AInput: Banana -> Output: BInput: Cherry -> Output: CWhen the user then provides the new input
Input: Grape, the model responds withOutput: G. The user was expecting the output to be the full wordGrape.Which of the following best explains why the model produced an unexpected result?
Constructing an Effective Input-Output Pattern
Predicting Model Behavior from a Few-Shot Pattern