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  "path": "/t/resonant-intelligence-born-rule-fusion-of-large-language-model-ensembles-quantum-inspired-interference-for-llm-ensembles/173951#post_1",
  "publishedAt": "2026-03-02T15:15:15.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "Resonant Intelligence: Born Rule Fusion of Large Language Model Ensembles"
  ],
  "textContent": "I’ve published a theoretical framework for combining LLM ensemble outputs using Born’s rule from quantum mechanics, producing bilinear interference cross-terms that no existing ensemble method generates.\n\n## The Problem\n\nEvery current ensemble method (averaging, log-linear, routing, majority vote) combines models linearly — the relationship between model predictions is ignored.\n\n## The Idea\n\nConvert each model’s token probability into a complex amplitude ψ(t) = √P(t) · e^(iφ), superpose them, and extract the combined probability via |Σψ|². This produces interference terms √(Pᵢ·Pⱼ)·cos(φᵢ−φⱼ) that:\n\n  * Amplify tokens where models agree (constructive interference)\n  * Suppress tokens where models disagree (destructive interference)\n  * Can push combined probability **below** any individual model’s estimate — impossible with any weighted average\n\n\n\nThe phase φ is derived from the logit gap (top-1 minus top-2 logit), which is already available from any forward pass. No new information is needed — just a structurally different mathematical operation on existing outputs.\n\n## Paper\n\nResonant Intelligence: Born Rule Fusion of Large Language Model Ensembles\nDOI: 10.5281/zenodo.18836337\n\nThe paper includes a systematic comparison against DeePEn, FusionRoute, MoA, self-consistency, and all major ensemble classes — none produce these cross-terms. It also presents three potentially fatal problems with full rigour and proposes falsifiable experiments (Phase Coherence Test via Rayleigh statistic, Cross-Term Discrimination Test).\n\n## Looking For\n\n  * Feedback on the framework and phase extraction approach\n  * Collaborators interested in running the empirical validation (two open-weight models + 10K tokens is sufficient)\n  * Pointers to any prior work I may have missed\n\n\n\nHappy to discuss the maths, limitations, or experimental design.",
  "title": "Resonant Intelligence: Born Rule Fusion of Large Language Model Ensembles — Quantum-Inspired Interference for LLM Ensembles"
}