Prompt Framework

Prompt frameworks are designed to optimize the performance of large language models (LLMs) by carefully structuring input prompts. Current research focuses on developing hierarchical and adaptive prompting strategies, incorporating external knowledge sources like knowledge graphs, and tailoring prompts to specific tasks such as medical image analysis and logical query answering. These advancements aim to improve LLM accuracy, efficiency, and reliability across diverse applications, ultimately enhancing their utility in scientific research and practical domains.