# Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition

arXiv: https://arxiv.org/abs/2511.21731 · HTML: https://mlsanity.com/paper/2511.21731/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 137 references that are in the map.
- First posted on arXiv 21 Nov 2025.

## Builds on (most cited first, 14 of 14)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Quantum Structure in Cognition: Human Language as a Boson Gas of Entangled Words](https://mlsanity.com/paper/1909.06845/) (2019)
- [A Planck Radiation and Quantization Scheme for Human Cognition and Language](https://mlsanity.com/paper/2201.03306/) (2022)
- [Are Words the Quanta of Human Language? Extending the Domain of Quantum Cognition](https://mlsanity.com/paper/2110.04913/) (2021)
- [Quantum Entanglement in Concept Combinations](https://mlsanity.com/paper/1302.3831/) (2013)
- [Quantum entanglement in physical and cognitive systems: a conceptual analysis and a general representation](https://mlsanity.com/paper/1903.09103/) (2019)
- [The Quantum Nature of Identity in Human Thought: Bose-Einstein Statistics for Conceptual Indistinguishability](https://mlsanity.com/paper/1410.6854/) (2014)
- [Entanglement in Cognition violating Bell Inequalities Beyond Cirel'son's Bound](https://mlsanity.com/paper/2102.03847/) (2021)
- [Quantum Bose-Einstein Statistics for Indistinguishable Concepts in Human Language](https://mlsanity.com/paper/2103.15125/) (2021)
- [Toward a Quantum Theory of Humor](https://mlsanity.com/paper/1703.04647/) (2017)
- [Identifying Quantum Mechanical Statistics in Italian Corpora](https://mlsanity.com/paper/2412.07919/) (2024)
- [Bell's Inequalities and Entanglement in Corpora of Italian Language](https://mlsanity.com/paper/2505.02038/) (2025)

## Built on by (most cited first, 3 of 3)

- [Comment on arXiv:2511.21731v1: Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition](https://mlsanity.com/paper/2601.06104/) (2026)
- [Auditing Question-Order Effects in Large Language Models with the QQ Equality: Mechanism Characterization and a Saturation Caveat](https://mlsanity.com/paper/2607.17219/) (2026)
- [Reply to comments arXiv:2512.07881 and arXiv:2601.06104 on quantum structure in human and AI-generated language](https://mlsanity.com/paper/2609.25797/) (2026)

## Abstract (arXiv)

We present the results of cognitive tests on conceptual combinations, performed using specific Large Language Models (LLMs) as test subjects. In the first test, performed with ChatGPT and Gemini, we show that Bell's inequalities are significantly violated, which indicates the presence of a 'non-classical probability model' with probabilities that do not satisfy Kolmogorov's axioms. In the second test, also performed using ChatGPT and Gemini, we identify the presence of 'Bose-Einstein statistics', rather than the intuitively expected 'Maxwell-Boltzmann statistics', in the distribution of the words contained in large-size texts. Interestingly, these findings mirror the results previously obtained in both cognitive tests with human participants and information retrieval tests on large corpora. Taken together, they point to the 'systematic emergence of non-classical quantum-like structures in conceptual-linguistic domains', regardless of whether the cognitive agent is human or artificial. Although LLMs are classified as neural networks for historical reasons, we believe that a more essential form of knowledge organization takes place in the distributive semantic structure of vector spaces built on top of the neural network. It is this meaning-bearing structure that lends itself to a phenomenon of evolutionary convergence between human cognition and language, slowly established through biological evolution, and LLM cognition and language, emerging much more rapidly as a result of self-learning and training. We analyze various aspects and examples that contain evidence supporting the above hypothesis. We also advance a unifying framework that explains the pervasive quantum organization of meaning that we identify.