A team is using a state-of-the-art, highly consistent language model for a critical question-answering task. To maximize accuracy, they plan to use an ensembling technique: they will ask the same question using five slightly rephrased prompts and then aggregate the answers. Given the model's high consistency, what is the most probable result of this approach?
0
1
Tags
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
Science
Related
Strategy for Prompting a High-Performance Language Model
A team is using a state-of-the-art, highly consistent language model for a critical question-answering task. To maximize accuracy, they plan to use an ensembling technique: they will ask the same question using five slightly rephrased prompts and then aggregate the answers. Given the model's high consistency, what is the most probable result of this approach?
Evaluating an Ensembling Strategy for a Robust LLM