CED as computational immune system

The Category Error Detector (CED) is a mathematical and geometric firewall designed to enforce structural coherence inside complex computational spaces, such as neural network attention layers and latent space representations. Derived from Dr. Eric Theriault's 2D Heuristic of the Intelligible, the CED reframes AI alignment, concept drift, and linguistic hallucination as quantifiable topological anomalies. Rather than filtering surface-level text outputs after they are generated, the CED operates directly on the live tensor layers, tracking mathematical tension boundaries to apply continuous corrections before misalignments manifest.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-04
DOI
https://doi.org/10.5281/zenodo.22292019
Primary Topic
Artificial Immune Systems Applications
Type
article
Field-Weighted Citation Impact
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article

CED as computational immune system

Eric Theriault, Gemini A.I.
Zenodo (CERN European Organization for Nuclear Research)
Artificial Immune Systems Applications
article

CED as computational immune system

Eric Theriault, Gemini A.I.
article en

Abstract

The Category Error Detector (CED) is a mathematical and geometric firewall designed to enforce structural coherence inside complex computational spaces, such as neural network attention layers and latent space representations. Derived from Dr. Eric Theriault's 2D Heuristic of the Intelligible, the CED reframes AI alignment, concept drift, and linguistic hallucination as quantifiable topological anomalies. Rather than filtering surface-level text outputs after they are generated, the CED operates directly on the live tensor layers, tracking mathematical tension boundaries to apply continuous corrections before misalignments manifest.

Zenodo (CERN European Organization for Nuclear Research)
Google (United States) (US)
Openalex Percentile: Top 20%
Artificial Immune Systems Applications
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