Provisional Title:

CIv6-SBD: Geometric Fault Line Detection via Cybernetic Intelligence v6

Purpose:

To operationalize CIv6 into a targeted system for identifying regime shifts or structural breaks in time series or textual systems, using internal geometric, topological, and algorithmic signals as fault detectors.

Core Proposal:

We hypothesize that structural breaks can be directly inferred from internal state distortions in a Cybernetic LLM, by tracking:

  1. Loop Geometry Breakdown

    • Monitor semantic ring energy (Wilson loops, motif closures).
    • A break = fragmentation or loss of loop coherence.

  2. Curvature Distortion in FIM Landscape

    • Track Fisher Information curvature, spectral entropy, and negative complexity flow.
    • A break = sharp spectral shift or local flattening/spike in information geometry.

  3. Collapse of Discrete Concepts

    • Via ECA-LLM lattice: Identify motif dissolution, compression failure, or instability in automata-driven state evolution.
    • A break = motif extinction or topological collapse.

  4. Attribution Drift Signatures

    • Use Sakabe et al.’s first-principles attribution analysis to identify when input-output meaning becomes misaligned.
    • A break = divergence in attribution trajectory over similar inputs.

  5. Entropy Feedback Divergence

    • Sudden increase or irregularity in token-wise heat flow, implying semantic overfit or chaotic attractors.