MBPM: Mimicry Beyond Pattern Matching in Large Language Models and Biomimetic Pathways Toward Meta-Awareness

Recent evaluations of large language models (LLMs) on mathematical reasoning benchmarks have revealed systematic brittleness under controlled distributional shifts. The GSM-Symbolic benchmark demonstrated that state-of-the-art models suffer substantial accuracy drops when numerical values are altered or when a single irrelevant but superficially plausible clause is inserted, supporting the hypothesis that current LLMs function primarily as sophisticated statistical mimicry engines rather than as systems performing genuine logical inference [1]. We examine the implications of this finding for classical arguments that artificial systems are subject to Gödel’s incompleteness theorems. Because the observed behaviour does not correspond to the operation of a consistent formal axiomatic system capable of expressing arithmetic, the incompleteness results do not apply in the same direct manner as they would to a formal prover. Building on principles of biological and molecular mimicry, we propose that explicit architectural mechanisms for high-fidelity template matching and higher-order self-modeling may improve robustness to distractors and furnish functional proxies for meta-awareness. We implement a controlled toy simulation comparing a MimicryNet architecture (incorporating affinity-based gating and a self-model head) against standard multilayer perceptron, LSTM, and transformer baselines on synthetic arithmetic tasks that reproduce the core perturbations of GSM-Symbolic. While overall arithmetic accuracy remains limited by model scale, the mimicry-enhanced architecture acquires reliable detection of distractors (self-model accuracy ≥ 0.95). We discuss the conceptual links between molecular-affinity mechanisms, higher-order thought theories of consciousness, and the possibility that sufficiently precise mimicry of the dynamical signatures of conscious processing could support reportable meta-awareness. Limitations of the toy regime and the speculative nature of any consciousness claim are stated explicitly.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-17
DOI
https://doi.org/10.5281/zenodo.21978386
Primary Topic
Embodied and Extended Cognition
Type
preprint
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MBPM: Mimicry Beyond Pattern Matching in Large Language Models and Biomimetic Pathways Toward Meta-Awareness

Martin Noirmont
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
preprint

MBPM: Mimicry Beyond Pattern Matching in Large Language Models and Biomimetic Pathways Toward Meta-Awareness

Martin Noirmont
preprint en

Abstract

Recent evaluations of large language models (LLMs) on mathematical reasoning benchmarks have revealed systematic brittleness under controlled distributional shifts. The GSM-Symbolic benchmark demonstrated that state-of-the-art models suffer substantial accuracy drops when numerical values are altered or when a single irrelevant but superficially plausible clause is inserted, supporting the hypothesis that current LLMs function primarily as sophisticated statistical mimicry engines rather than as systems performing genuine logical inference [1]. We examine the implications of this finding for classical arguments that artificial systems are subject to Gödel’s incompleteness theorems. Because the observed behaviour does not correspond to the operation of a consistent formal axiomatic system capable of expressing arithmetic, the incompleteness results do not apply in the same direct manner as they would to a formal prover. Building on principles of biological and molecular mimicry, we propose that explicit architectural mechanisms for high-fidelity template matching and higher-order self-modeling may improve robustness to distractors and furnish functional proxies for meta-awareness. We implement a controlled toy simulation comparing a MimicryNet architecture (incorporating affinity-based gating and a self-model head) against standard multilayer perceptron, LSTM, and transformer baselines on synthetic arithmetic tasks that reproduce the core perturbations of GSM-Symbolic. While overall arithmetic accuracy remains limited by model scale, the mimicry-enhanced architecture acquires reliable detection of distractors (self-model accuracy ≥ 0.95). We discuss the conceptual links between molecular-affinity mechanisms, higher-order thought theories of consciousness, and the possibility that sufficiently precise mimicry of the dynamical signatures of conscious processing could support reportable meta-awareness. Limitations of the toy regime and the speculative nature of any consciousness claim are stated explicitly.

Zenodo (CERN European Organization for Nuclear Research)
Institute of Labour and Social Studies (PL)
Embodied and Extended Cognition
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MBPM: Mimicry Beyond Pattern Matching in Large Language Models and Biomimetic Pathways Toward Meta-Awareness — Martin Noirmont · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS