# ProMoAI: Process Modeling with Generative AI

arXiv: https://arxiv.org/abs/2403.04327 · HTML: https://mlsanity.com/paper/2403.04327/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 32 references that are in the map.
- First posted on arXiv 7 Mar 2024.

## Builds on (most cited first, 14 of 14)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Least-to-Most Prompting Enables Complex Reasoning in Large Language Models](https://mlsanity.com/paper/2205.10625/) (2022)
- [Large Language Models Are Human-Level Prompt Engineers](https://mlsanity.com/paper/2211.01910/) (2022)
- [Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models](https://mlsanity.com/paper/2305.16807/) (2023)
- [ExpertPrompting: Instructing Large Language Models to be Distinguished Experts](https://mlsanity.com/paper/2305.14688/) (2023)
- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [Large Language Models can accomplish Business Process Management Tasks](https://mlsanity.com/paper/2307.09923/) (2023)
- [SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models](https://mlsanity.com/paper/2303.10464/) (2023)
- [Parameter-Efficient Sparsity for Large Language Models Fine-Tuning](https://mlsanity.com/paper/2205.11005/) (2022)
- [Large Language Models for Business Process Management: Opportunities and Challenges](https://mlsanity.com/paper/2304.04309/) (2023)
- [Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study](https://mlsanity.com/paper/2307.02194/) (2023)
- [Just Tell Me: Prompt Engineering in Business Process Management](https://mlsanity.com/paper/2304.07183/) (2023)
- [PET: An Annotated Dataset for Process Extraction from Natural Language Text](https://mlsanity.com/paper/2203.04860/) (2022)
- [A Composable Just-In-Time Programming Framework with LLMs and FBP](https://mlsanity.com/paper/2308.00204/) (2023)

## Built on by (most cited first, 12 of 12)

- [PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Tasks](https://mlsanity.com/paper/2407.13244/) (2024)
- [Leveraging Large Language Models for Enhanced Process Model Comprehension](https://mlsanity.com/paper/2408.08892/) (2024)
- [Structured Extraction from Business Process Diagrams Using Vision-Language Models](https://mlsanity.com/paper/2511.22448/) (2025)
- [BPMN Assistant: An LLM-Based Approach to Business Process Modeling](https://mlsanity.com/paper/2509.24592/) (2025)
- [What is the Best Process Model Representation? A Comparative Analysis for Process Modeling with Large Language Models](https://mlsanity.com/paper/2507.11356/) (2025)
- [Knowledge-Driven Hallucination in Large Language Models: An Empirical Study on Process Modeling](https://mlsanity.com/paper/2509.15336/) (2025)
- [Assessing the Business Process Modeling Competences of Large Language Models](https://mlsanity.com/paper/2601.21787/) (2026)
- [Automatic Generation of Executable BPMN Models from Medical Guidelines](https://mlsanity.com/paper/2604.07817/) (2026)
- [Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text](https://mlsanity.com/paper/2605.24546/) (2026)
- [LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines](https://mlsanity.com/paper/2606.09489/) (2026)
- [Design and Implementation of Agentic Orchestrations and Orchestration of Agents](https://mlsanity.com/paper/2606.31518/) (2026)
- [LLM-based Vulnerability Discovery in Business Process Documentation](https://mlsanity.com/paper/2608.04271/) (2026)

## Abstract (arXiv)

ProMoAI is a novel tool that leverages Large Language Models (LLMs) to automatically generate process models from textual descriptions, incorporating advanced prompt engineering, error handling, and code generation techniques. Beyond automating the generation of complex process models, ProMoAI also supports process model optimization. Users can interact with the tool by providing feedback on the generated model, which is then used for refining the process model. ProMoAI utilizes the capabilities LLMs to offer a novel, AI-driven approach to process modeling, significantly reducing the barrier to entry for users without deep technical knowledge in process modeling.