Improving Sarcasm Detection in a Language Model
An analyst is using a language model to classify customer feedback. The model correctly classifies straightforward comments but fails on sarcastic ones. For example, when given the prompt Classify the sentiment of this feedback as Positive, Negative, or Neutral: 'Oh fantastic, my package arrived a week late. Just what I wanted.', the model incorrectly responds Positive. Design a new, single prompt that incorporates a step-by-step reasoning process to guide the model to the correct answer for this specific feedback.
0
1
Tags
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Step-by-Step Calculation of the Average of 2, 4, and 9
A user wants a language model to solve the following word problem: 'A store had 50 shirts. They sold 15 on Monday and then received a new shipment of 25 on Tuesday. How many shirts do they have now?' The model consistently gives an incorrect answer. Based on principles for improving model accuracy, which of the following revised prompts is the most effective for guiding the model to the correct solution?
Improving Sarcasm Detection in a Language Model
Optimizing an AI Travel Itinerary Generator