Semantic Compression With Large Language Models

no code implementations • 25 Apr 2023 • Henry Gilbert, Michael Sandborn, Douglas C. Schmidt, Jesse Spencer-Smith, Jules White

The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks.

Code Generation Information Retrieval +2

ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design

no code implementations • 11 Mar 2023 • Jules White, Sam Hays, Quchen Fu, Jesse Spencer-Smith, Douglas C. Schmidt

This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate common software engineering activities, such as ensuring code is decoupled from third-party libraries and simulating a web application API before it is implemented.

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

no code implementations • 21 Feb 2023 • Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, Douglas C. Schmidt

This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs.

Prompt Engineering Transfer Learning