AI Model Explainer for Non-Numerical Data Types
Summary
The USPTO published patent application US20260099763A1 by inventors Wan et al. covering mechanisms for AI model explanation of non-numerical data. The system converts non-numerical feature data into numerical representations, processes these through an AI model explainer to generate explanations, and converts outputs back to non-numerical form using two trained computer models.
What changed
The USPTO published patent application US20260099763A1 covering an AI model explainer system for non-numerical data types. The system uses a first trained model to convert non-numeric feature data into numeric representations, inputs these into an AI model explainer to generate explanations, and uses a second trained model to convert the numeric explanation outputs back to non-numeric representations.
Technology companies developing AI/ML systems, particularly those focused on model interpretability and explainability, should monitor this application. While patent applications do not create immediate compliance obligations, they signal technical approaches that may become industry standards or affect future product development strategies.
What to do next
- Monitor for updates if developing AI explainability systems
Archived snapshot
Apr 10, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
ARTIFICIAL INTELLIGENCE MODEL EXPLAINER FOR NON-NUMERICAL DATA TYPES
Application US20260099763A1 Kind: A1 Apr 09, 2026
Inventors
Meng Wan, Xiang Yu Xue, Sheng Yan Sun, Mai Zeng
Abstract
Mechanisms are provided for performing an artificial intelligence (AI) model explainer for an AI computer model. The mechanisms receive input data comprising non-numeric feature data, which may be results generated by the AI computer model. The mechanisms process the non-numeric feature data via a first computer model trained to convert non-numeric feature data into a numeric representation of the non-numeric feature data. The mechanisms input the numeric representation of the non-numeric feature data into the AI model explainer to generate an AI model explanation output having a portion corresponding to the numeric representation of the non-numeric feature data. The mechanisms process the AI model explanation output via a second computer model that is trained to convert the portion from the numeric representation to an output non-numeric representation consistent with the non-numeric feature data and the converted output may then be output.
CPC Classifications
G06N 20/00
Filing Date
2024-10-08
Application No.
18909233
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