Manuscript · 2026International Conference on Industrialized Construction

ConstructionQA: Evaluating Multimodal Large Language Models on Industrial Construction Drawing Set

Obiora Odugu, Mohammad Hadi Foroozandeh Dehkordi, Asif Faisal Chowdhury, Muhammad Tahir Khan, Chao Wang

All research records

Research summary

A task-specific benchmark for multimodal answers about construction drawings.

Research record

This record preserves the title and author order of the supplied manuscript. Its research stage remains separate from the existence of a PDF or conference-formatted layout.

Evaluation results, cohort definitions, limitations, and source locators are maintained in the related project. This record does not duplicate the project metrics.

Evaluation Scope & Methodology

Samples, denominators, uncertainty, sources and limits

Approach

Compare models within each task and supplied-context condition; do not pool different task metrics.

Results and scope belong to the related case study, ConstructionQA: reading supplied drawing context.

Cohorts and samples

CohortSampleDefinition
ConstructionQA supplied-context questions120 question–answer pairsApproximately 150+ sheets across eight disciplines; task-specific subsets.

Reported measures

MeasureUnitCohortDenominatorUncertaintyEvidence
Information extraction F1-BoW, GPT-5.4Score from 0 to 1ConstructionQA supplied-context questionsInformation-extraction task subset of the 120-pair benchmarkNone reportedReported in source
Information extraction F1-BoW, Gemini 2.5 FlashScore from 0 to 1ConstructionQA supplied-context questionsInformation-extraction task subset of the 120-pair benchmarkNone reportedReported in source
Cross-discipline coordination combined score, GPT-5.4Score from 0 to 1ConstructionQA supplied-context questionsCross-discipline coordination task subset, Table 1None reportedReported in source
Sheet-reference F1: GPT-5.4Score from 0 to 1ConstructionQA supplied-context questionsSame ConstructionQA sheet-reference task under distractor and guaranteed-context conditionsNone reportedReported in source
Sheet-reference F1: Gemini 2.5 FlashScore from 0 to 1ConstructionQA supplied-context questionsSame ConstructionQA sheet-reference task under distractor and guaranteed-context conditionsNone reportedReported in source
Sheet-reference F1: GPT-4.1 NanoScore from 0 to 1ConstructionQA supplied-context questionsSame ConstructionQA sheet-reference task under distractor and guaranteed-context conditionsNone reportedReported in source

Limitations

  • Supplied relevant sheets do not test full-corpus retrieval.
  • Guaranteed context does not improve every task.
  • Native-PDF conditions are separate from Table 1.

Sources

  • ConstructionQA: Evaluating Multimodal Large Language Models on Industrial Construction Drawing Set, Benchmark description; Table 1; Figure 2 (Supplied manuscript reviewed November 2026). Open approved PDF

Cite this record

Obiora Odugu, Mohammad Hadi Foroozandeh Dehkordi, Asif Faisal Chowdhury, Muhammad Tahir Khan, Chao Wang. ConstructionQA: Evaluating Multimodal Large Language Models on Industrial Construction Drawing Set. International Conference on Industrialized Construction. Manuscript, 2026.

Formatted from the supplied manuscript. Publisher metadata has not been verified, so no BibTeX is offered yet.

LSU Industrial Training & Assessment Center · September 2024 to present

Energy Assessment Team Leader & Researcher

I lead industrial energy assessments: utility-bill analysis, on-site measurement, energy-balance calculations, and client technical reports. Totals are team assessment outcomes.

Recommended annual electricity savings

8,208,899 kWh/year

16 assessments with recommendations

Implemented annual electricity savings

5,950,754 kWh/year

11 assessments with implementation reports