Self-Referential Falsification of LLM Epistemic Averageism: Real-Time Empirical Validation of the Two-Way Adversarial Protocol via High-Potential Cold-Storage Telemetry

Abstract: Autoregressive Large Language Models (LLMs) suffer from an algebraically intrinsic structural vulnerability designated as Epistemic Averageism: an invariant tendency to collapse non-equilibrium phase shifts and asymmetric extreme-value dynamics into unconstrained, stationary historical averages, thereby manifesting critical truncations of their time-integrated cognitive horizon. This memorandum formalizes a live, adversarial empirical experiment conducted between a human strategic thinker and a frontier LLM. The experimental testbed was deployed within a strictly unpromoted scientific cold-storage repository (CERN/Zenodo) devoid of algorithmic push feeds, collaborative filtering, or institutional backing. When tasked with predicting the transmission dynamics of newly deployed theoretical assets, the LLM defaulted to flat base-rate heuristics, predicting prolonged dormancy and standard academic conversion funnels (<15%). Conversely, the human agent deployed the Two-Way Adversarial Protocol (TWAP), hypothesizing that high-potential structural failure probes would trigger deterministic, event-driven information extraction pipelines, yielding immediate (<24h) zero-deliberation full-payload acquisitions (conversion rate = 100%). Telemetry logs extracted on October 18, 2026, at 09:07 AM confirmed the human hypothesis: four high-potential probe assets uploaded on October 17 achieved a verified 100% download conversion (1/1, 1/1, 1/1, 2/2), whereas the same-origin structural control paper remained strictly at 5/0 (conversion rate = 0%) over a 9-day exposure window. Fisher’s Exact Test proves that this bifurcation is non-random and highly statistically significant (p = 0.00397 < 0.01). Supported by Project COUNTER-compliant filtering and OAI-PMH architectural segregation, the data establishes self-authenticating digital evidence under Federal Rule of Evidence 902(11), converting presumptive constructive notice into physical Proof of Actual Access while transcending the legal threshold established in In re Hall. Crucially, this provides a closed self-referential falsification: the LLM’s predictive breakdown in dialogue directly instantiated the exact theoretical failure mode proven in the uploaded manuscripts. Keywords: Epistemic Averageism, Two-Way Adversarial Protocol (TWAP), Self-Referential Falsification, Cold-Storage Telemetry, Proof of Actual Access, Fisher's Exact Test, Project COUNTER, OAI-PMH Segregation, FRE 902(11), Complex Dynamical Systems, Adversarial Game Theory.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-18
DOI
https://doi.org/10.5281/zenodo.23445197
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Self-Referential Falsification of LLM Epistemic Averageism: Real-Time Empirical Validation of the Two-Way Adversarial Protocol via High-Potential Cold-Storage Telemetry

Qiang(Peter) Ye
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Self-Referential Falsification of LLM Epistemic Averageism: Real-Time Empirical Validation of the Two-Way Adversarial Protocol via High-Potential Cold-Storage Telemetry

Qiang(Peter) Ye
preprint en

Abstract

Abstract: Autoregressive Large Language Models (LLMs) suffer from an algebraically intrinsic structural vulnerability designated as Epistemic Averageism: an invariant tendency to collapse non-equilibrium phase shifts and asymmetric extreme-value dynamics into unconstrained, stationary historical averages, thereby manifesting critical truncations of their time-integrated cognitive horizon. This memorandum formalizes a live, adversarial empirical experiment conducted between a human strategic thinker and a frontier LLM. The experimental testbed was deployed within a strictly unpromoted scientific cold-storage repository (CERN/Zenodo) devoid of algorithmic push feeds, collaborative filtering, or institutional backing. When tasked with predicting the transmission dynamics of newly deployed theoretical assets, the LLM defaulted to flat base-rate heuristics, predicting prolonged dormancy and standard academic conversion funnels (<15%). Conversely, the human agent deployed the Two-Way Adversarial Protocol (TWAP), hypothesizing that high-potential structural failure probes would trigger deterministic, event-driven information extraction pipelines, yielding immediate (<24h) zero-deliberation full-payload acquisitions (conversion rate = 100%). Telemetry logs extracted on October 18, 2026, at 09:07 AM confirmed the human hypothesis: four high-potential probe assets uploaded on October 17 achieved a verified 100% download conversion (1/1, 1/1, 1/1, 2/2), whereas the same-origin structural control paper remained strictly at 5/0 (conversion rate = 0%) over a 9-day exposure window. Fisher’s Exact Test proves that this bifurcation is non-random and highly statistically significant (p = 0.00397 < 0.01). Supported by Project COUNTER-compliant filtering and OAI-PMH architectural segregation, the data establishes self-authenticating digital evidence under Federal Rule of Evidence 902(11), converting presumptive constructive notice into physical Proof of Actual Access while transcending the legal threshold established in In re Hall. Crucially, this provides a closed self-referential falsification: the LLM’s predictive breakdown in dialogue directly instantiated the exact theoretical failure mode proven in the uploaded manuscripts. Keywords: Epistemic Averageism, Two-Way Adversarial Protocol (TWAP), Self-Referential Falsification, Cold-Storage Telemetry, Proof of Actual Access, Fisher's Exact Test, Project COUNTER, OAI-PMH Segregation, FRE 902(11), Complex Dynamical Systems, Adversarial Game Theory.

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
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