AI Visibility Boundary and Non-Equivalence Theorem

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: Joseph Mas
DOI: 10.5281/zenodo.18465021
Cited by: 0

Abstract

This theorem establishes formal boundary conditions and non-equivalence constraints within AI Visibility, clarifying that downstream metrics, rankings, and performance indicators are not substitutes for upstream learning conditions in large language model training systems.

Fields of Study & Subjects

Topic Modeling Artificial Intelligence Applications Natural Language Processing Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
19 January 2026