Prompt Augmentation

Prompt augmentation is a technique used to improve the performance of large language models (LLMs) and other AI systems by strategically modifying or expanding the input prompts. Current research focuses on automatically generating high-quality augmentations using LLMs themselves, exploring various augmentation strategies like paraphrasing, adding descriptive details, and incorporating contextual information to address issues like hallucinations and data scarcity. This approach enhances model performance across diverse tasks, including image captioning, audio classification, named entity recognition, and question answering, ultimately leading to more robust and efficient AI systems.