SysTemp: A Multi-Agent System for Template-Based Generation of SysML v2
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866911025800937472 |
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| author | Bouamra, Yasmine Yun, Bruno Poisson, Alexandre Armetta, Frédéric |
| author_facet | Bouamra, Yasmine Yun, Bruno Poisson, Alexandre Armetta, Frédéric |
| contents | The automatic generation of SysML v2 models represents a major challenge in the engineering of complex systems, particularly due to the scarcity of learning corpora and complex syntax. We present SysTemp, a system aimed at facilitating and improving the creation of SysML v2 models from natural language specifications. It is based on a multi-agent system, including a template generator that structures the generation process. We discuss the advantages and challenges of this system through an evaluation, highlighting its potential to improve the quality of the generations in SysML v2 modeling. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_21608 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SysTemp: A Multi-Agent System for Template-Based Generation of SysML v2 Bouamra, Yasmine Yun, Bruno Poisson, Alexandre Armetta, Frédéric Computation and Language Artificial Intelligence The automatic generation of SysML v2 models represents a major challenge in the engineering of complex systems, particularly due to the scarcity of learning corpora and complex syntax. We present SysTemp, a system aimed at facilitating and improving the creation of SysML v2 models from natural language specifications. It is based on a multi-agent system, including a template generator that structures the generation process. We discuss the advantages and challenges of this system through an evaluation, highlighting its potential to improve the quality of the generations in SysML v2 modeling. |
| title | SysTemp: A Multi-Agent System for Template-Based Generation of SysML v2 |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2506.21608 |