ARTIFICIAL CONTENT IDENTIFICATION USING SUBSET SCANNING OVER GENERATIVE MODEL ACTIVATIONS

A processor may receive input data. The processor may train a first machine learning model with the input data to extract a group of activation nodes. The processor may extract the group of activation nodes. The processor may detect anomalous nodes from the group of activation nodes.

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Bibliographic Details
Main Authors Akinwande, Victor Abayomi, Weldemariam, Komminist, Cintas, Celia, SPEAKMAN, Skyler, Tadesse, Girmaw Abebe
Format Patent
LanguageEnglish
Published 05.05.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:A processor may receive input data. The processor may train a first machine learning model with the input data to extract a group of activation nodes. The processor may extract the group of activation nodes. The processor may detect anomalous nodes from the group of activation nodes.
Bibliography:Application Number: US202017090116