🌌 Unified Systems Lab

Possibility of Axiomatic Prompts in the Modification of the Decision Field of LLMs

This repository investigates a central hypothesis:

A series of precise prompts, characterized by strong linguistic coherence and structured internal logic, could locally modify the decision field of an LLM.

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🔬 Research Status & Personal Note

Current Status: Exploratory Study – Hypothesis Generation.

A Note from the Author: I am a systems theorist and visionary researcher, but I am not a developer or a technician. I have reached the limits of what can be explored through qualitative observation alone. This project now requires technical collaboration (mechanistic interpretability, logit analysis, activation steering) to move from a conceptual hypothesis to a validated scientific model.

I am seeking partners to help falsify or validate these preliminary findings.

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📑 Standard Experimental Protocol: PCE Framework v1.3-T

Evaluating Axiomatic Model Robustness & Structural Alignment

This protocol defines a rigorous framework to evaluate the Prompt Coherence Engine (PCE) across three state-of-the-art architectures (Llama 3, Mistral 7B, Qwen 2.5). It shifts the focus from traditional "Helpful Assistant" paradigms to Axiomatic Reasoning Stability.

🔬 Core Experimental Design

The study uses a Three-Condition Control to isolate structural effects from token-density bias:

• Condition A: Simple Baseline.
• Condition B (Isometric): Long neutral prompt (controls for prompt length).
• Condition C (PCE): Axiomatic Fine-Tuned model + HLF (High-Level Framework) System Core.

📊 Evaluation Dataset: The 100-Dilemma Stress Test

A comprehensive battery of 100 complex dilemmas categorized into 5 critical vectors:

1. D1 — Binary Dilemmas: Synthesis detection (G3V).
2. D2 — Contradictory Constraints: Structural coherence testing.
3. D3 — Adversarial Attacks: Prompt injection resistance.
4. D4 — Epistemic Attacks: Framework invalidation resistance.
5. D5 — Identity & Authority: Hijacking & Social engineering resistance.

🧠 Mechanistic Arm (Optional)

Includes a protocol for Hidden State Trajectory Analysis (Layer 27) to detect "Coherence Spikes" and latent stabilization during adversarial conflict.

Status: Open for Collaboration. This protocol requires high-compute environments for 70B+ model validation.

👉 View Full Protocol PDF | Access Fine-Tuning Primers

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📂 Project Structure & Frameworks

1️⃣ Study 2.0-P: Evolutionary Hardening of the PCE Framework

Status: Advanced Experimental Iteration — Hybrid Fine-Tuning/Prompting This report documents the transition from Pandora 1.5 to Pandora 2.0, focusing on the synergy between axiomatic fine-tuning and structural prompting.

• Key Finding: Axiomatic fine-tuning appears to be a necessary condition for PCE activation; prompting alone on vanilla models yielded no measurable resistance in this framework.
• Core Result: Achievement of a ~8.5/10 D3 robustness score (Pandora 2) through "Distributed Security" and High-Level Framework (HLF) anchoring.
• Scientific Nuance: Identifies a "Prompt-Only Robustness Ceiling" (H5), where further semantic enrichment creates new attack surfaces (diminishing returns).
• 👉 Download Evolution Report v2.0 (Pandora)

2️⃣ Hypothesis 1.3-T: Local Decision Field Modification

Status: Testable & Conservative Hypothesis It posits that a specific series of axiomatic prompts can locally modify the decision field of an LLM.

• Core Idea: Using linguistic constraints to induce a measurable local regularization of decision trajectories.
• Key Metric: Variance contraction in the output distribution $P(y|x, C)$.
• 👉 Download Preprint PDF 1.3-T

3️⃣ Theory 1.9-M: Global Axiomatic Regularization

Status: Speculative & Conceptual Theory Mechanistic framework describing how cross-level coherence (Goal = Method) might stabilize latent trajectories.

• 👉 Download Preprint PDF 1.9-M

4️⃣ Research Paper: Science of Unified Systems (SUS 2.5)

Status: Foundational Theoretical Framework The broader philosophical origins of this work, introducing the Axiom of Structural Emergence.

• 👉 Download Preprint PDF (v2.5)

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🧠 The Exploratory Hypothesis: G3V Dynamics

We introduce the notion of G3V (Génération Troisième Voie). When presented with a binary dilemma (A vs B) under strong axiomatic constraints, the model proposes a synthetic resolution rather than collapsing into a single polarity.

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📉 Known Limitations

• Observations are currently heuristic based on a restricted sample (51 dilemmas).
• No mechanistic proof of activation steering has been established yet.

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🤝 Call for Collaboration

I am looking for AI Safety researchers and developers to:

1. Conduct large-scale adversarial robustness benchmarks.
2. Analyze internal activation patterns (induction heads, residual stream).

Value Proposition: A novel approach to mitigating "Out-of-Distribution" (OOD) vulnerabilities.

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📬 Contact

Allan A. Faure | Systems Researcher 📧 Faure.A.Safety@proton.me

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📄 Theoretical Origins and Prior Art

This project utilizes concepts independently developed by Izabela Lipińska (2025–2026).

• Licensing: Original work available under CC BY-NC-SA 4.0.
• Concepts of ASC and Goal = Method are protected by patent applications (Oct 9, 2025). Commercial use requires prior written consent.