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Few-Shot Prompting

Also known as: In-Context Learning, Few-Shot Learning

A technique for guiding large language models by providing a small number of examples within the input prompt to demonstrate the desired task or output format. In accessibility applications, few-shot prompting can help AI systems perform context-specific tasks like correcting captioning errors by showing examples from the current conversation, enabling the model to learn domain vocabulary and speaking patterns without requiring fine-tuning or retraining.

Category: Artificial Intelligence · Natural Language Processing

Related: Large Language Model

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