Enhancing Language Models Through Prompt Engineering - A Survey

In recent years, language models have undergone significant advancements with models like GPT-3, showcasing impressive abilities in natural language processing and generation. However, these models often experience from issues such as generating biased or unreliable content, producing inappropriate responses, or failing to fulfill specific user needs. To address these challenges, prompt engineering emerged as a promising approach by providing explicit guidance to language models. It refers to the process of designing and constructing effective prompts or instructions to guide language models like GPT-3 in generating desired outputs. In this article an attempt was made to address the role of prompt engineering, its techniques, and its potential impact on enhancing the performance and reliability of language models.