This paper provides a comprehensive overview of efficient prompting methods for large language models (LLMs). Prompting is a crucial paradigm for adapting LLMs to specific natural language processing (NLP) tasks, but it often involves computational overhead and manual design of complex prompts. The authors categorize efficient prompting methods into two main approaches: efficient computation and efficient design. Efficient computation methods focus on compressing prompts to reduce computational costs, while efficient design methods aim to automatically optimize prompts. The paper reviews various techniques, including knowledge distillation, encoding, filtering, gradient-based optimization, and evolutionary algorithms. It highlights the challenges of lengthy and complex prompts and discusses future research directions, emphasizing the need for multi-objective optimization to balance prompt compression and task accuracy. The paper concludes by providing a list of open-source projects and a typology diagram to aid researchers and practitioners in the field.This paper provides a comprehensive overview of efficient prompting methods for large language models (LLMs). Prompting is a crucial paradigm for adapting LLMs to specific natural language processing (NLP) tasks, but it often involves computational overhead and manual design of complex prompts. The authors categorize efficient prompting methods into two main approaches: efficient computation and efficient design. Efficient computation methods focus on compressing prompts to reduce computational costs, while efficient design methods aim to automatically optimize prompts. The paper reviews various techniques, including knowledge distillation, encoding, filtering, gradient-based optimization, and evolutionary algorithms. It highlights the challenges of lengthy and complex prompts and discusses future research directions, emphasizing the need for multi-objective optimization to balance prompt compression and task accuracy. The paper concludes by providing a list of open-source projects and a typology diagram to aid researchers and practitioners in the field.