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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2408.02087 |
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| _version_ | 1866911977121513472 |
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| author | Lu, Jiaxing Li, Heran Ning, Fangwei Wang, Yixuan Li, Xinze Shi, Yan |
| author_facet | Lu, Jiaxing Li, Heran Ning, Fangwei Wang, Yixuan Li, Xinze Shi, Yan |
| contents | Since ancient times, mechanical design aids have been developed to assist human users, aimed at improving the efficiency and effectiveness of design. However, even with the widespread use of contemporary Computer-Aided Design (CAD) systems, there are still high learning costs, repetitive work, and other challenges. In recent years, the rise of Large Language Models (LLMs) has introduced new productivity opportunities to the field of mechanical design. Yet, it remains unrealistic to rely on LLMs alone to complete mechanical design tasks directly. Through a series of explorations, we propose a method for constructing a comprehensive Mechanical Design Agent (MDA) by guiding LLM learning. To verify the validity of our proposed method, we conducted a series of experiments and presented relevant cases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_02087 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Constructing Mechanical Design Agent Based on Large Language Models Lu, Jiaxing Li, Heran Ning, Fangwei Wang, Yixuan Li, Xinze Shi, Yan Computational Engineering, Finance, and Science Since ancient times, mechanical design aids have been developed to assist human users, aimed at improving the efficiency and effectiveness of design. However, even with the widespread use of contemporary Computer-Aided Design (CAD) systems, there are still high learning costs, repetitive work, and other challenges. In recent years, the rise of Large Language Models (LLMs) has introduced new productivity opportunities to the field of mechanical design. Yet, it remains unrealistic to rely on LLMs alone to complete mechanical design tasks directly. Through a series of explorations, we propose a method for constructing a comprehensive Mechanical Design Agent (MDA) by guiding LLM learning. To verify the validity of our proposed method, we conducted a series of experiments and presented relevant cases. |
| title | Constructing Mechanical Design Agent Based on Large Language Models |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2408.02087 |