806 citations · 857 across the 7 of their papers we have counts for
4 papers · 1 filter
Semantic Compression With Large Language Models
Henry Gilbert, Michael Sandborn, Douglas C. Schmidt +2
The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks. However, in addition to confidently…
ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design
Jules White, Sam Hays, Quchen Fu +2
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…
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
Jules White, Quchen Fu, Sam Hays +6
Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LL…
NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
Quchen Fu, Zhongwei Teng, Marco Georgaklis +2
Translating natural language into Bash Commands is an emerging research field that has gained attention in recent years. Most efforts have focused on producing more accurate transl…