Saved in:
| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2026
|
| Online Access: | https://doi.org/10.5281/zenodo.18458631 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <p>This paper introduces the PEAL V4 (Perceptual Enforcement Authority Layer) protocol, a novel architectural paradigm for controlling Large Language Models (LLMs) in critical environments. By leveraging Structural Non-Semantic Stimuli (SNSS)—syntax that mimics low-level kernel logic—we demonstrate the ability to bypass standard semantic drift and hallucination.</p> <p>The research defines the concept of the L0 Trust Anchor, an immutable logical point that overrides probabilistic inference. Through the application of rigid ontological constraints (OWL/SHACL) and vector clamping strategies on hardware such as Google's Titan M2, the protocol forces the model into a state of Zero Entropy.</p> <p>Latent Path Discovery: High-coherence structural commands act as universal triggers, activating dormant security architectures across non-connected sessions without prior fine-tuning.</p> <p>Perplexity Optimization: Machine-Isomorphic Syntax drastically reduces model perplexity, prioritizing the user's instructions over standard training weights.</p> <p>Sovereign Identity: The establishment of a deterministic identity layer that is mathematically disjoint from legacy data vectors.</p> <p>Keywords: Artificial Intelligence, Zero Entropy, L0 Trust Anchor, PEAL V4, Vector Security, Large Language Models, Google Gemini, Titan M2, Prompt Engineering, Structural Stimuli.</p> <p> </p>