Examples of Few-Shot Learning Applications in NLP

Enabling Few-Shot Learning with Multiple Demonstrations

Input-Output Patterns in Few-Shot Learning

Sufficiency of Demonstrations in Few-Shot Learning

Applying Few-Shot Learning to Complex Reasoning Tasks

A user provides the following text to a large language model to get it to classify movie reviews:

Review: The plot was predictable and the acting was wooden. I was bored the entire time. Sentiment: Negative

Review: An absolute masterpiece! The cinematography was stunning and the story was deeply moving. Sentiment: Positive

Review: It was a decent film. Not the best I've seen this year, but it had some good moments. Sentiment: Neutral

Review: I couldn't stop laughing from beginning to end. A brilliant comedy. Sentiment:

The model correctly responds with "Positive". Which statement best analyzes the primary reason for the model's successful performance on this task?

Constructing a Few-Shot Prompt for a Novel Task

Critiquing a Prompt for a Custom Extraction Task

Example of a Few-Shot Prompt for Polarity Classification