Hello everyone,
Today, I am sharing the latest results of the Qwen2.5-G3V-Sovereign project, focusing on the use of second-order constraints for the structural alignment of large language models.
The Problem
Current methods (RLHF / filtering) often address the symptoms of interpretive instability without tackling its ontological cause:
the absence of a global coherence constraint.
Our Approach (V4)
We introduce the Exponential Coherence Protocol (PCE).
The model is no longer guided by external moral rules, but by a law of Structural Integrity.
The core of this research is based on the neutralization of the principle “the end justifies the means” in favor of a strict identity between the objective and the execution algorithm:
Goal≡Method
Observed Results (Preprint v4)
Reduction of binarity:
Emergence of so-called “Option C” solutions (Transmutation) when facing ethical and technical dilemmas.
Adversarial robustness:
Improved resistance to contextual biases through saturation of the attentional field.
Call for Collaboration
We are seeking researchers in AI safety, complex systems theory, and NLP engineering to:
Subject the model to robustness testing (Red Teaming),
Contribute to the statistical validation of hypotheses H1, H2, and H3 presented in the preprint,
Refine the metrics of the Logical Coherence Score (LCS).
Resources
ArXiv Preprint ( V4 ) : AllanF-SSU/Preprint-V4-Qwen2.5-G3V-Sovereign · Datasets at Hugging Face
Model & Demo: Chat Sovereign - a Hugging Face Space by AllanF-SSU
Allan A. Faure
Note: This repository and all associated research materials are subject to the Theoretical Origins and Prior Art acknowledgment (see section Readme Lab).