Reply to comments arXiv:2512.07881 and arXiv:2601.06104 on quantum structure in human and AI-generated language
cs.CL
Submitted: 2026-09-22
Updated: 2026-09-22
Comments: Reply to comments arXiv:2512.07881 and arXiv:2601.06104, 6 pages
License: http://creativecommons.org/licenses/by/4.0/
The gist: We reply to the comments by M.
Terminology
Abstract
We reply to the comments by M. Sienicki and K. Sienicki (arXiv:2512.07881) and by K. Sienicki (arXiv:2601.06104) on our work on quantum-mechanical statistics in human language (arXiv:2407.14924) and on quantum structure in AI-generated language (arXiv:2511.21731). We thank the authors for their careful reading and address what we consider to be the main points of criticism: the exploratory nature of the protocol used in the experiments with large language models; the role of marginal-law violations, and of the Contextuality-by-Default criterion, in the identification of entanglement; the limited diagnostic value of a Bose-Einstein fit taken in isolation; the meaning of assigning the lowest energy levels to the most frequent words; and the relation between the vector spaces used by LLMs and quantum state spaces. We also correct a typographical error in Table 3 of arXiv:2511.21731, which does not affect the reported CHSH value.
Sources
- Revised comment on the paper titled "The Origin of Quantum Mechanical Statistics: Insights from Research on Human Language
- Comment on arXiv:2511.21731v1: Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition
- The Origin of Quantum Mechanical Statistics: Some Insights from the Research on Human Language
- Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition
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