2023-03-15 · preprint · Topic Modeling · en
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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.
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This work is a preprint concerned with topic modeling. Because it is a preprint, it has not yet cleared peer review, so its claims should be weighted as preliminary rather than established.
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This work was produced by a small team of three researchers.
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The work has received 2391 citations, marking it as already an established reference point in its field. It references 0 works.
3 cited facts
GPT-4 Technical Report is a preprint, focusing on Topic Modeling, published in 2023.
GPT-4 Technical Report has 2,391 citations in our record, placing it among the highly cited works we track.
Our record lists 3 authors for GPT-4 Technical Report. Author names aren't in our data yet — the source link on the page lists the full byline.
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