In-context learning is a form of few-shot learning where a model is provided with a small number of input-label pairs as examples, allowing the model to recognize a task and provide an answer for a query without parameter updates.

Authors

• Person: Not available Organization: arXiv
  A Survey on the Theory and Mechanism of Large Language Models

Sources

• A Survey on the Theory and Mechanism of Large Language Models arxiv.org arXiv via serper

Referenced by nodes (2)

• In-Context Learning concept
• few-shot learning concept