GPT-4Glass Box AIMFOUR Vibe FrameworkVibe Integrity Scorelarge language models
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Abstract (AI)
Abstract—Large Language Models (LLMs) suffer from inherent stochasticity, limiting their utility in high-stakes enterprise environments where determinism and auditability are required. This paper introduces the MFOUR Vibe Framework (MVF), a platform-agnostic architectural standard that transforms probabilistic natural language intent into deterministic software artifacts. We define a five-layer topology, comprising the Kernel Identity, Synaptic Routing, Interface Contracts, Context Anchoring, and the Mirror Test. Furthermore, we introduce The Vibe Integrity Score (VIS), a quantitative metric for evaluating the structural adherence of generative outputs. This specification provides the foundational schema and logic protocols for building "Glass Box" AI systems that are observable, secure, and commercially viable.
Key Findings
1
MVF defines a five-layer architecture: Kernel Identity, Synaptic Routing, Interface Contracts, Context Anchoring, and the Mirror Test.
2
The MFOUR Vibe Framework transforms probabilistic natural-language intent into deterministic software artifacts for enterprise applications.
3
The Vibe Integrity Score provides a quantitative metric for evaluating structural adherence in generative outputs.
4
The abstract identifies LLM stochasticity as a limitation for high-stakes environments requiring determinism and auditability.
5
The framework establishes foundational schemas and logic protocols for observable, secure, and commercially viable “Glass Box” AI systems.
Research Object
MFOUR Vibe Framework (MVF) — a platform-agnostic architectural standard for transforming probabilistic natural language intent into deterministic software artifacts
Research Subject
the five-layer architectural topology and the Vibe Integrity Score (VIS) for deterministic transformation, structural adherence, observability, and auditability of generative outputs
Publication Details
Publication Date
2023-03-15
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