The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition

Fuente: arXiv
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Autori principali: Pichat, Michael, Pogrund, William, Gasparian, Armanush, Pichat, Paloma, Demarchi, Samuel, Veillet-Guillem, Michael, Corbet, Martin, Dasilva, Théo
Natura: Preprint
Pubblicazione: 2025
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author Pichat, Michael
Pogrund, William
Gasparian, Armanush
Pichat, Paloma
Demarchi, Samuel
Veillet-Guillem, Michael
Corbet, Martin
Dasilva, Théo
author_facet Pichat, Michael
Pogrund, William
Gasparian, Armanush
Pichat, Paloma
Demarchi, Samuel
Veillet-Guillem, Michael
Corbet, Martin
Dasilva, Théo
contents This article investigates, within the field of neuropsychology of artificial intelligence, the process of categorical segmentation performed by language models. This process involves, across different neural layers, the creation of new functional categorical dimensions to analyze the input textual data and perform the required tasks. Each neuron in a multilayer perceptron (MLP) network is associated with a specific category, generated by three factors carried by the neural aggregation function: categorical priming, categorical attention, and categorical phasing. At each new layer, these factors govern the formation of new categories derived from the categories of precursor neurons. Through a process of categorical clipping, these new categories are created by selectively extracting specific subdimensions from the preceding categories, constructing a distinction between a form and a categorical background. We explore several cognitive characteristics of this synthetic clipping in an exploratory manner: categorical reduction, categorical selectivity, separation of initial embedding dimensions, and segmentation of categorical zones.
format Preprint
id arxiv_https___arxiv_org_abs_2502_15710
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition
Pichat, Michael
Pogrund, William
Gasparian, Armanush
Pichat, Paloma
Demarchi, Samuel
Veillet-Guillem, Michael
Corbet, Martin
Dasilva, Théo
Artificial Intelligence
Neurons and Cognition
This article investigates, within the field of neuropsychology of artificial intelligence, the process of categorical segmentation performed by language models. This process involves, across different neural layers, the creation of new functional categorical dimensions to analyze the input textual data and perform the required tasks. Each neuron in a multilayer perceptron (MLP) network is associated with a specific category, generated by three factors carried by the neural aggregation function: categorical priming, categorical attention, and categorical phasing. At each new layer, these factors govern the formation of new categories derived from the categories of precursor neurons. Through a process of categorical clipping, these new categories are created by selectively extracting specific subdimensions from the preceding categories, constructing a distinction between a form and a categorical background. We explore several cognitive characteristics of this synthetic clipping in an exploratory manner: categorical reduction, categorical selectivity, separation of initial embedding dimensions, and segmentation of categorical zones.
title The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition
topic Artificial Intelligence
Neurons and Cognition
url https://arxiv.org/abs/2502.15710