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Resonant Intelligence: Born Rule Fusion of Large Language Model Ensembles

OpenAlex
Authors: Aaron Jessop

Year

2026

Paper ID

25439

Status

Preprint

Abstract Read

~2 min

Abstract Words

106

Citations

0

Abstract

A theoretical framework proposing Born Rule Fusion (BRF) for combining large language model ensemble outputs using quantum-inspired interference. BRF introduces bilinear cross-terms modulated by phase cosines — a structural operation absent from all surveyed ensemble methods. Three potentially fatal problems are presented with equal rigour. The framework is falsifiable: a concrete phase coherence test using the Rayleigh statistic is specified. All conceptual contributions are the sole responsibility of the author. v2 (2026-03-03): Corrected Council of AIs accuracy figures to match primary source; fixed citation numbering in Section 7; added normalisation assumption parenthetical in Section 3.1; de-duplicated Weinberg discussion across Sections 2.2 and 5.5; resolved orphan lines at three page boundaries.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • A theoretical framework proposing Born Rule Fusion (BRF) for combining large language model ensemble outputs using quantum-inspired interference.

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Current Paper #25439 #69034 Hardware-aware Low-latency Quan... #69003 QBugLM: An Agentic Benchmarking... #68993 Tomography of quantum states wi... #68978 Repair Before Veto, When Repair...

External citation index: OpenAlex citation signal • updated 2026-06-19 12:46:51

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