From over-reliance to smart integration: using Large-Language Models as translators between specialized modeling and simulation tools
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912427302453248 |
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| author | Giabbanelli, Philippe J. Beverley, John David, Istvan Tolk, Andreas |
| author_facet | Giabbanelli, Philippe J. Beverley, John David, Istvan Tolk, Andreas |
| contents | Large Language Models (LLMs) offer transformative potential for Modeling & Simulation (M&S) through natural language interfaces that simplify workflows. However, over-reliance risks compromising quality due to ambiguities, logical shortcuts, and hallucinations. This paper advocates integrating LLMs as middleware or translators between specialized tools to mitigate complexity in M&S tasks. Acting as translators, LLMs can enhance interoperability across multi-formalism, multi-semantics, and multi-paradigm systems. We address two key challenges: identifying appropriate languages and tools for modeling and simulation tasks, and developing efficient software architectures that integrate LLMs without performance bottlenecks. To this end, the paper explores LLM-mediated workflows, emphasizes structured tool integration, and recommends Low-Rank Adaptation-based architectures for efficient task-specific adaptations. This approach ensures LLMs complement rather than replace specialized tools, fostering high-quality, reliable M&S processes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_11141 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From over-reliance to smart integration: using Large-Language Models as translators between specialized modeling and simulation tools Giabbanelli, Philippe J. Beverley, John David, Istvan Tolk, Andreas Software Engineering Emerging Technologies Large Language Models (LLMs) offer transformative potential for Modeling & Simulation (M&S) through natural language interfaces that simplify workflows. However, over-reliance risks compromising quality due to ambiguities, logical shortcuts, and hallucinations. This paper advocates integrating LLMs as middleware or translators between specialized tools to mitigate complexity in M&S tasks. Acting as translators, LLMs can enhance interoperability across multi-formalism, multi-semantics, and multi-paradigm systems. We address two key challenges: identifying appropriate languages and tools for modeling and simulation tasks, and developing efficient software architectures that integrate LLMs without performance bottlenecks. To this end, the paper explores LLM-mediated workflows, emphasizes structured tool integration, and recommends Low-Rank Adaptation-based architectures for efficient task-specific adaptations. This approach ensures LLMs complement rather than replace specialized tools, fostering high-quality, reliable M&S processes. |
| title | From over-reliance to smart integration: using Large-Language Models as translators between specialized modeling and simulation tools |
| topic | Software Engineering Emerging Technologies |
| url | https://arxiv.org/abs/2506.11141 |