LLM Reference
Concepts & capability filters
learning_paradigm

Few-shot learning

Few-shot learning enables large language models to perform tasks effectively using only a small number of labeled examples (typically 1-10) provided in the prompt, relying on in-context learning without parameter updates.

Category
learning_paradigm
Difficulty
Not classified
Aliases
None tracked
Last reviewed
2026-07-02

Key facts

  • It bridges the gap between zero-shot and fine-tuning by demonstrating patterns through examples.

Models Mentioning Few-shot learning(7)