Retrieval Augmented Generation

This is a method that enhances text generation by integrating retrieval-based and generation-based techniques to produce more accurate and relevant outputs. It works by retrieving pertinent information from a vast corpus and utilizing it to inform the generation process, thereby improving the quality of the generated text. Retrieval Augmented Generation is particularly beneficial for applications requiring precise and contextually relevant responses, such as in customer support or information retrieval systems.

Retrieval Augmented Generation was discovered on October 7th 2024 and it currently has a search volume of 49.5K with a growth of +99X+.