Neuropsychology of AI: Relationship Between Activation Proximity and Categorical Proximity Within Neural Categories of Synthetic Cognition
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Abstract (arXiv)
Neuropsychology of artificial intelligence focuses on synthetic neural cog nition as a new type of study object within cognitive psychology. With the goal of making artificial neural networks of language models more explainable, this approach involves transposing concepts from cognitive psychology to the interpretive construction of artificial neural cognition. The human cognitive concept involved here is categorization, serving as a heuristic for thinking about the process of segmentation and construction of reality carried out by the neural vectors of synthetic cognition.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 8 of its 61 references that are in the map. First posted on arXiv 8 Oct 2024.
Builds on
8 of 61 references.
References · 8
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Citing papers per year: 2025: 3.
3 papers.
- 2025Synthetic Categorical Restructuring large Or How AIs Gradually Extract Efficient Regularities from Their Experience of the Worldcited by 2
- 2025Intra-neuronal attention within language models Relationships between activation and semanticscited by 0
- 2025Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spacescited by 0
- 2025Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces30 Apr 2025
- 2025Intra-neuronal attention within language models Relationships between activation and semantics17 Mar 2025
- 2025Synthetic Categorical Restructuring large Or How AIs Gradually Extract Efficient Regularities from Their Experience of the World25 Feb 2025