AEC-Bench: A Multimodal Benchmark for Agentic Systems in Architecture, Engineering, and Construction
arXiv AIArchived Apr 01, 2026✓ Full text saved
arXiv:2603.29199v1 Announce Type: new Abstract: The AEC-Bench is a multimodal benchmark for evaluating agentic systems on real-world tasks in the Architecture, Engineering, and Construction (AEC) domain. The benchmark covers tasks requiring drawing understanding, cross-sheet reasoning, and construction project-level coordination. This report describes the benchmark motivation, dataset taxonomy, evaluation protocol, and baseline results across several domain-specific foundation model harnesses. W
Full text archived locally
✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 31 Mar 2026]
AEC-Bench: A Multimodal Benchmark for Agentic Systems in Architecture, Engineering, and Construction
Harsh Mankodiya, Chase Gallik, Theodoros Galanos, Andriy Mulyar
The AEC-Bench is a multimodal benchmark for evaluating agentic systems on real-world tasks in the Architecture, Engineering, and Construction (AEC) domain. The benchmark covers tasks requiring drawing understanding, cross-sheet reasoning, and construction project-level coordination. This report describes the benchmark motivation, dataset taxonomy, evaluation protocol, and baseline results across several domain-specific foundation model harnesses. We use AEC-Bench to identify consistent tools and harness design techniques that uniformly improve performance across foundation models in their own base harnesses, such as Claude Code and Codex. We openly release our benchmark dataset, agent harness, and evaluation code for full replicability at this https URL under an Apache 2 license.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2603.29199 [cs.AI]
(or arXiv:2603.29199v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2603.29199
Focus to learn more
Submission history
From: Andriy Mulyar [view email]
[v1] Tue, 31 Mar 2026 03:10:28 UTC (7,806 KB)
Access Paper:
HTML (experimental)
view license
Current browse context:
cs.AI
< prev | next >
new | recent | 2026-03
Change to browse by:
cs
References & Citations
NASA ADS
Google Scholar
Semantic Scholar
Export BibTeX Citation
Bookmark
Bibliographic Tools
Bibliographic and Citation Tools
Bibliographic Explorer Toggle
Bibliographic Explorer (What is the Explorer?)
Connected Papers Toggle
Connected Papers (What is Connected Papers?)
Litmaps Toggle
Litmaps (What is Litmaps?)
scite.ai Toggle
scite Smart Citations (What are Smart Citations?)
Code, Data, Media
Demos
Related Papers
About arXivLabs
Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)