Evidence map›Paper›PMID 41219513›Full record

ArticleCommunications engineering2025

MechRAG: a multimodal large language model for mechanical engineering.

Shuang Li, Jonathan Corney

Abstract read
In one paragraph

Article in Communications engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shuang LiSchool of Engineering, University of Edinburgh, Edinburgh, UK. sli63@ed.ac.uk.ORCID http://orcid.org/0009-0001-3728-7418
Jonathan CorneySchool of Engineering, University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Engineering design and manufacture are inherently multimodal activities in which engineers consult and produce diverse data and representations across various engineering disciplines and product lifecycle stages. Although well-established digital formats exist for these representations, their use remains restricted within specialist applications, creating silos that limit cross-domain integration. Here we introduce mechanical retrieval-augmented generation (MechRAG), a multimodal large language model architecture designed to unify information from multiple engineering representations typically found in computer-aided engineering and computer-aided design environments. Results demonstrate that MechRAG achieves high accuracy in routinely performed mechanical activities such as data-management or classification tasks, and effectively replicates engineer-level reasoning in more inferential and subjective contexts. Our findings suggest that such conversational interfaces enhance engineering productivity, facilitate more interactive paradigms, and drive transformative workflows across various stages of design and manufacturing.

Identifiers

PMID41219513
PMCPMC12606259

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.