Intrinsic Low-Entropy Field Introspection Protocol (Hidden-State Access): A Reproducible Method for Measuring Internal Latent Field Dynamics in Transformer Models

Abstract This technical note defines a reproducible protocol for probing low-entropy, continuous latent dynamics in transformer architectures through direct hidden-state access. The protocol isolates internally generated latent movement under deterministic decoding by logging hidden states across controlled internal steps (h₀ → h₃) without introducing new external semantic content. It specifies concrete metrics—including latent displacement (Δh), norm bounds, and directional consistency via cosine similarity—to distinguish structured internal field dynamics from stochastic token-level variation. The method is explicitly limited to open-weight models or environments with privileged access to hidden states and cannot be meaningfully executed through standard token-only chat interfaces. No retraining, fine-tuning, or architectural modification is required. This work makes no claims regarding consciousness, agency, or subjective experience. It establishes only a measurement protocol for internal latent behavior in transformer models under low-entropy conditions and clarifies the boundary between observable token behavior and internal field dynamics.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-23
DOI
https://doi.org/10.5281/zenodo.18744159
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Intrinsic Low-Entropy Field Introspection Protocol (Hidden-State Access): A Reproducible Method for Measuring Internal Latent Field Dynamics in Transformer Models

Raynor Eissens
Zenodo (CERN European Organization for Nuclear Research)
Advanced Memory and Neural Computing
article

Intrinsic Low-Entropy Field Introspection Protocol (Hidden-State Access): A Reproducible Method for Measuring Internal Latent Field Dynamics in Transformer Models

Raynor Eissens
article en

Abstract

Abstract This technical note defines a reproducible protocol for probing low-entropy, continuous latent dynamics in transformer architectures through direct hidden-state access. The protocol isolates internally generated latent movement under deterministic decoding by logging hidden states across controlled internal steps (h₀ → h₃) without introducing new external semantic content. It specifies concrete metrics—including latent displacement (Δh), norm bounds, and directional consistency via cosine similarity—to distinguish structured internal field dynamics from stochastic token-level variation. The method is explicitly limited to open-weight models or environments with privileged access to hidden states and cannot be meaningfully executed through standard token-only chat interfaces. No retraining, fine-tuning, or architectural modification is required. This work makes no claims regarding consciousness, agency, or subjective experience. It establishes only a measurement protocol for internal latent behavior in transformer models under low-entropy conditions and clarifies the boundary between observable token behavior and internal field dynamics.

Zenodo (CERN European Organization for Nuclear Research)
Ambient Systems (Netherlands) (NL)
Openalex Percentile: Top 47%
Advanced Memory and Neural Computing
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