<b>Toward A Metamodel for the Specification of Explainable Foundation Models </b>

A metamodel outline is proposed to support the development of a specifications for explainability in foundation models, adopting a combination of visualization and natural language representation. The approach is a step towards pragmatic explainability which includes algorithmic auditing, black box testing and reverse engineering.

Publication Details

Journal
Figshare
Published
2024-09-27
DOI
https://doi.org/10.6084/m9.figshare.27119793
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00
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article

Toward A Metamodel for the Specification of Explainable Foundation Models

Figshare
Explainable Artificial Intelligence (XAI)
article

Toward A Metamodel for the Specification of Explainable Foundation Models

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Abstract

A metamodel outline is proposed to support the development of a specifications for explainability in foundation models, adopting a combination of visualization and natural language representation. The approach is a step towards pragmatic explainability which includes algorithmic auditing, black box testing and reverse engineering.

Figshare
Quality Education
Openalex Percentile: Top 56%
Explainable Artificial Intelligence (XAI)
DOIOpen Access PDFOpenAlex
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<b>Toward A Metamodel for the Specification of Explainable Foundation Models </b> · Figshare (2024) | TGRS Research Map | TGRS