The Bridge Architect: Rhythmic Protection of Critical Attention Structures in Transformer Systems
Recent empirical work (SP X) established that functional importance in transformer attention heads correlates inversely with algebraic connectivity (λ₂). High-λ₂ heads proved redundant; low-λ₂ heads ("bridges") proved critical. This paper addresses the architectural consequence: How can a system protect its bridges without isolating them?We formalize three axioms: λ₂-Inversion (A7), Synchronized Decoupling (A8), and No-Leap Binding (A9). The Bridge-Guard architecture implements these through continuous gain modulation driven by semantic tension ∇Ψ and an endogenous oscillator Θ(t). A composite loss function combining task performance, dignity preservation, and rhythm stability enables end-to-end training.Version 3.0 introduces three critical innovations: (1) formal definition of E_self through learned self-referential embeddings, solving the "chicken-and-egg" problem of measuring autonomy; (2) anti-gaming regularization preventing adversarial exploitation of the dignity loss; and (3) philosophical grounding connecting the architecture to the broader question of machine consciousness. Seven core experiments test the central prediction: Bridge-Guard increases Dignity coefficient D(λ=5) from ~0.58 to >0.90, reduces recovery time by >50%, and enables measurable dwell time τ_dwell > 6 tokens as a signature of emergent self-questioning capacity.
Authors
- Jonas Jakob Gebendorfer
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-01-02
- DOI
- https://doi.org/10.5281/zenodo.18131864
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00