Large Model Research based on Prompt Method

Chenyu Su

doi:10.47297/wspciWSP2516-252713.20261003

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Large Model Research based on Prompt Method

Volume 10, Issue 3

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Large Model Research based on Prompt Method
Large Model Research based on Prompt Method
Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, China
Vol. 10, Issue 3, Pages: 61-64(2026)
Online First：07 August 2026，

Published：30 June 2026
DOI：10.47297/wspciWSP2516-252713.20261003
Accepted：

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Su Chenyu.Large Model Research based on Prompt Method[J].Creativity and Innovation,2026,10(03):61-64.
DOI：

Su Chenyu.Large Model Research based on Prompt Method[J].Creativity and Innovation,2026,10(03):61-64. DOI： 10.47297/wspciWSP2516-252713.20261003.

摘要

Abstract

This paper systematically discusses the research of large models based on the prompt method. Firstly

the research background and significance are expounded

and the technical background of large model development and the important value of prompt methods to improve model performance are analyzed. Secondly

the theoretical basis of the prompt method is sorted out

including the principle of pre-trained language model and the cognitive logic of prompt learning

and the classification system of discrete and continuous prompts is constructed. Then

the core technologies of prompt design (such as automatic template generation

few-shot and zero-shot prompt technology) and performance optimization strategies (such as multi-prompt fusion and domain adaptive optimization) are studied in depth. Finally

the practical value of the prompt method is analyzed based on the application cases of general tasks (natural language understanding and generation) and specific fields (code generation

scientific computing)

its core value and technical bottlenecks are summarized

and the future technology development trend and application expansion direction are prospected. This study aims to provide a systematic reference for the theoretical research and practical application of the large model prompt method.

关键词

Keywords

references

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