Context operations to architecture modelling output from large language models and evaluation criteria for their use in systems engineering design — Paper

Abstract

The development of generative artificial intelligence resources enables opportunities of speeding up systems and engineering design work. This contribution introduces a framework of formal operations for assembling context in LLM-based engineering design. This framework involves the assembly of modular context units, including policy prompts, reference units with persistence, and user questions with prompt vectoring. This approach enables the systematic structuring of interactions with generative models. A formal method for evaluating modelling-as-code LLM outputs is also presented, which enables the evaluation of compliance to intent from LLM answers and thereby asses the support from LLMs for systems architecture modelling.

Authors 2

Vinicius Kaster Marini, Petter Krus

Specification

Official page: arxiv.org/abs/2609.10132
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Arxiv announce type: cross
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
arXiv id: 2609.10132
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Categories: eess.SY, cs.AI, cs.SE, cs.SY
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
PDF: arxiv.org/pdf/2609.10132
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Primary category: eess.SY
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

5 h ago

Conflicts

None

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Authors: Vinicius Kaster Marini, Petter Krus

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Claim history · Abstract

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Claim history for Abstract
Value	Valid from → to	Status	Source	Confidence	Extractor
The development of generative artificial intelligence resources enables opportunities of speeding up systems and engineering design work. This contribution introduces a framework of formal operations for assembling context in LLM-based engineering design. This framework involves the assembly of modular context units, including policy prompts, reference units with persistence, and user questions with prompt vectoring. This approach enables the systematic structuring of interactions with generative models. A formal method for evaluating modelling-as-code LLM outputs is also presented, which enables the evaluation of compliance to intent from LLM answers and thereby asses the support from LLMs for systems architecture modelling.	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
New paperPaperContext operations to architecture modelling output from large language models and evaluation criteria for their use in systems engineering design
New paper: Context operations to architecture modelling output from large language models and evaluation criteria for their use in systems engineering design
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Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.AI	feed	T1· Official	3 h ago	1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.