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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.04327 |
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| _version_ | 1866929451936251904 |
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| author | Kourani, Humam Berti, Alessandro Schuster, Daniel van der Aalst, Wil M. P. |
| author_facet | Kourani, Humam Berti, Alessandro Schuster, Daniel van der Aalst, Wil M. P. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_04327 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ProMoAI: Process Modeling with Generative AI Kourani, Humam Berti, Alessandro Schuster, Daniel van der Aalst, Wil M. P. Databases Computation and Language 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. |
| title | ProMoAI: Process Modeling with Generative AI |
| topic | Databases Computation and Language |
| url | https://arxiv.org/abs/2403.04327 |