## PM4Py.LLM: a Comprehensive Module for Implementing PM on LLMs
> you can go to the [paper](https://arxiv.org/pdf/2404.06035).
<p>paper describes the approaches that is implemented in the library PM4PY (Process Modeling For Python).</p>
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## Process Modeling With Large Language Models
> you can go to the [paper](https://arxiv.org/pdf/2403.07541v1).
### overview
<p>
this paper introduced advanced techniques in prompt engineering, error handling, and code generation to transform textual process descriptions into process models illustrating the described processes. and the framework features an interactive feedback loop, allowing for refining the generated models based on the user’s feedback.
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NOTE: it transforms the textual description to intermidate language (POWL) then to BPMN.</p>
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## Chit-Chat or Deep Talk: Prompt Engineering for Process Mining
> you can go to the [paper](https://arxiv.org/pdf/2307.09909).
