# An Exploration of Pattern Mining with ChatGPT

arXiv: https://arxiv.org/abs/2412.16814 · HTML: https://mlsanity.com/paper/2412.16814/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 16 references that are in the map.
- First posted on arXiv 22 Dec 2024.

## Builds on (most cited first, 1 of 1)

- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)

## Built on by (most cited first, 1 of 1)

- [Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution](https://mlsanity.com/paper/2606.08800/) (2026)

## Abstract (arXiv)

This paper takes an exploratory approach to examine the use of ChatGPT for pattern mining. It proposes an eight-step collaborative process that combines human insight with AI capabilities to extract patterns from known uses. The paper offers a practical demonstration of this process by creating a pattern language for integrating Large Language Models (LLMs) with data sources and tools. LLMs, such as ChatGPT, are a new class of AI models that have been trained on large amounts of text, and can create new content, including text, images, or video. The paper also argues for adding affordances of the underlying components as a new element of pattern descriptions. The primary audience of the paper includes pattern writers interested in pattern mining using LLMs.