Representation Degeneration and Attention Saturation: The Structural Mechanics of Context Erasure in Autonomous Verification Substrates

This repository contains the technical preprint and formal verification modules addressing representation geometry, attention mechanisms, and algorithmic safety frameworks for autonomous verification substrates. Abstract This paper investigates attention saturation and dimensional collapse—systemic mathematical vulnerabilities in transformer-based autonomous substrates where soft-argmax (Softmax) operations degrade high-dimensional context representations under operational stress. We demonstrate that under extreme or conflicting boundary constraints, logit variances scale arbitrarily, causing the entropy of the self-attention matrix to collapse to zero. This behavior forces the attention allocation to behave like a discrete one-hot basis vector, effectively blinding the model to marginal probabilities and multi-variable constraints. This structural context erasure represents a foundational engineering failure mode that directly compromises systemic compliance with the principles of distinction and proportionality under International Humanitarian Law (IHL). We contrast these architectural limitations with the vulnerabilities of post-hoc statistical alignment techniques (such as RLHF) and present an upstream developer environment upgrade featuring a computer-checked Coq verification module (JargonFilter) that proves zero-leakage safety boundaries for data streams. Key Contributions • The Attention Saturation Framework: A rigorous analysis of entropy collapse and the singularity invariant of the Softmax Jacobian matrix (\(1 \in \ker(J)\)) under high operational stress. • Formal Verification Sandbox: A complete implementation and proof inside the Coq proof assistant (Module JargonFilter) closing the safety invariant theorem (zero_jargon_leakage). • Upstream Policy Validation: Shifting the challenge of algorithmic accountability from surface-level application patching to hardware-enforced compilation constraints under IHL. https://github.com/Borealiscodes/CoQ-Hallucination-Guard/blob/main/tex/COQwrapped/capacity_exhaustion_wrapper.v https://github.com/Borealiscodes/CoQ-Hallucination-Guard/blob/main/tex/COQwrapped/Jargon%20filter.v

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-02
DOI
https://doi.org/10.5281/zenodo.23883798
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Representation Degeneration and Attention Saturation: The Structural Mechanics of Context Erasure in Autonomous Verification Substrates

Hedling Borealis
6 links
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Representation Degeneration and Attention Saturation: The Structural Mechanics of Context Erasure in Autonomous Verification Substrates

Hedling Borealis
preprint en

Abstract

This repository contains the technical preprint and formal verification modules addressing representation geometry, attention mechanisms, and algorithmic safety frameworks for autonomous verification substrates. Abstract This paper investigates attention saturation and dimensional collapse—systemic mathematical vulnerabilities in transformer-based autonomous substrates where soft-argmax (Softmax) operations degrade high-dimensional context representations under operational stress. We demonstrate that under extreme or conflicting boundary constraints, logit variances scale arbitrarily, causing the entropy of the self-attention matrix to collapse to zero. This behavior forces the attention allocation to behave like a discrete one-hot basis vector, effectively blinding the model to marginal probabilities and multi-variable constraints. This structural context erasure represents a foundational engineering failure mode that directly compromises systemic compliance with the principles of distinction and proportionality under International Humanitarian Law (IHL). We contrast these architectural limitations with the vulnerabilities of post-hoc statistical alignment techniques (such as RLHF) and present an upstream developer environment upgrade featuring a computer-checked Coq verification module (JargonFilter) that proves zero-leakage safety boundaries for data streams. Key Contributions • The Attention Saturation Framework: A rigorous analysis of entropy collapse and the singularity invariant of the Softmax Jacobian matrix (\(1 \in \ker(J)\)) under high operational stress. • Formal Verification Sandbox: A complete implementation and proof inside the Coq proof assistant (Module JargonFilter) closing the safety invariant theorem (zero_jargon_leakage). • Upstream Policy Validation: Shifting the challenge of algorithmic accountability from surface-level application patching to hardware-enforced compilation constraints under IHL. https://github.com/Borealiscodes/CoQ-Hallucination-Guard/blob/main/tex/COQwrapped/capacity_exhaustion_wrapper.v https://github.com/Borealiscodes/CoQ-Hallucination-Guard/blob/main/tex/COQwrapped/Jargon%20filter.v

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
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Representation Degeneration and Attention Saturation: The Structural Mechanics of Context Erasure in Autonomous Verification Substrates — Hedling Borealis · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS