Large language models in industrial energy auditing: current state, architectural gaps, and the path to programmatic accuracy
Research summary
A literature synthesis of six gaps between model output and decision-grade audit reports.
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.
The current supplied review lists four authors. The older public review PDF has different authorship and is not linked as this version.
Evaluation Scope & Methodology
Samples, denominators, uncertainty, sources and limits
Approach
Preserve literature-selection denominators and distinguish synthesis judgments from measured system performance.
Results and scope belong to the related case study, How language models fit industrial energy auditing.
Cohorts and samples
| Cohort | Sample | Definition |
|---|---|---|
| Literature selection flow | 265 identified records | 19 duplicates; 246 screened; 105 full texts; 44 full-text exclusions; 61 included papers. |
| Application-class mapping | 38 papers | Subset used for the application-class map, not the full included corpus. |
Reported measures
| Measure | Unit | Cohort | Denominator | Uncertainty | Evidence |
|---|---|---|---|---|---|
| Literature selection counts | Count | Literature selection flow | Reported selection stages; counts describe sequential pools, not additive categories | None reported | Reported in source |
Limitations
- This is a literature synthesis, not a new model-accuracy benchmark.
- The 38-paper application map is a subset of the 61 included papers.
- The newest supplied version has multiple authors; the older public review has different authorship.
- Qualitative comparison graphics are not empirical accuracy measurements.
Sources
- Large language models in industrial energy auditing: current state, architectural gaps, and the path to programmatic accuracy, Figure 2; Figure 10; printed gap-to-pipeline figure caption (Supplied manuscript reviewed November 2026). Public release pending
Cite this record
Asif Faisal Chowdhury, Muhammad Tahir Khan, Obiora Odugu, Chao Wang. Large language models in industrial energy auditing: current state, architectural gaps, and the path to programmatic accuracy. Manuscript.
Formatted from the supplied manuscript. Publisher metadata has not been verified, so no BibTeX is offered yet.