• Computer Science > Artificial Intelligence [Submitted on 30 Jan 2026] Title:Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems View PDF HTML (experimental)Abstract:We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design Structure Matrices (DSMs). • We test these methods on two distinct use cases – a power screwdriver and a CubeSat with known architectural references – evaluating their performance on two key tasks: determining relationships between predefined components, and the more complex challenge of identifying components and their subsequent relationships. • We measure the performance by assessing each element of the DSM and overall architecture. • Despite design and computational challenges, we identify opportunities for automated DSM generation, with all code publicly available for reproducibility and further feedback from the domain experts. • Current browse context: cs.AI References & Citations export BibTeX citation Loading… • Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (Wh
Computer Science > Artificial Intelligence [Submitted on 30 Jan 2026] Title:Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems View PDF HTML (experimental)Abstract:We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design Structure Matrices (DSMs).
Article Summaries:
- A recent study investigates how large language models (LLMs) combined with Retrieval‑Augmented Generation (RAG) and its graph‑based variant (GraphRAG) can automatically produce Design Structure Matrices (DSMs) for cyber‑physical systems. The authors applied the methods to two test cases-a power screwdriver and a CubeSat-evaluating the models on two tasks: (1) mapping relationships among pre‑defined components, and (2) discovering both components and their interrelations. Performance was measured by comparing each DSM element and the overall architecture against known references. Results show promising, though not perfect, automation of DSM creation, and the authors have released all code for community validation.
- Computer Science > Artificial Intelligence [Submitted on 30 Jan 2026] Title:Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems View PDF HTML (experimental)Abstract:We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design Structure Matrices (DSMs). We test these methods on two distinct use cases – a power screwdriver and a CubeSat with known architectural references – evaluating their performance on two key tasks: de
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