PM4Py.LLM: a Comprehensive Module for Implementing PM on LLMs
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913307087077376 |
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| author | Berti, Alessandro |
| author_facet | Berti, Alessandro |
| contents | pm4py is a process mining library for Python implementing several process mining (PM) artifacts and algorithms. It also offers methods to integrate PM with large language models (LLMs). This paper examines how the current paradigms of PM on LLM are implemented in pm4py, identifying challenges such as privacy, hallucinations, and the context window limit. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_06035 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PM4Py.LLM: a Comprehensive Module for Implementing PM on LLMs Berti, Alessandro Databases pm4py is a process mining library for Python implementing several process mining (PM) artifacts and algorithms. It also offers methods to integrate PM with large language models (LLMs). This paper examines how the current paradigms of PM on LLM are implemented in pm4py, identifying challenges such as privacy, hallucinations, and the context window limit. |
| title | PM4Py.LLM: a Comprehensive Module for Implementing PM on LLMs |
| topic | Databases |
| url | https://arxiv.org/abs/2404.06035 |