基于模型的工程中的多模态摘要：汽车软件开发案例研究
Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study
AI总结：
本研究探索多模态大语言模型在基于模型的工程（MBE）中理解和识别UML与EMF图表信息的能力，并通过汽车软件开发案例评估了多模态摘要提升MBE实践生产力与准确性的潜力与局限。
摘要：
整合来自不同数据模态信息的多模态摘要，为辅助理解各种流程内的信息提供了一种有前景的解决方案。然而，多模态摘要的应用与优势在基于模型的工程（MBE）中尚未受到广泛关注，而MBE利用形式化模型在整个工程生命周期中提升理解、验证和自动化，已成为复杂系统设计与开发的基石。MBE中的UML和EMF图表包含大量多模态信息及复杂关系数据。因此，本研究探索多模态大语言模型在MBE领域内的应用，以评估其理解和识别UML与EMF图表中嵌入的关系、特征及功能的能力。我们旨在展示多模态摘要提升MBE实践中生产力与准确性的变革性潜在收益及局限。所提方法在汽车软件开发背景下进行了评估，同时考虑了多种有前景的最先进模型。
英文摘要：
Multimodal summarization integrating information from diverse data modalities presents a promising solution to aid the understanding of information within various processes. However, the application and advantages of multimodal summarization have not received much attention in model-based engineering (MBE), where it has become a cornerstone in the design and development of complex systems, leveraging formal models to improve understanding, validation and automation throughout the engineering lifecycle. UML and EMF diagrams in model-based engineering contain a large amount of multimodal information and intricate relational data. Hence, our study explores the application of multimodal large language models within the domain of model-based engineering to evaluate their capacity for understanding and identifying relationships, features, and functionalities embedded in UML and EMF diagrams. We aim to demonstrate the transformative potential benefits and limitations of multimodal summarization in improving productivity and accuracy in MBE practices. The proposed approach is evaluated within the context of automotive software development, while many promising state-of-art models were taken into account.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
