Technical overview demonstrates a state-transition control architecture for generative AI, highlighting selective verification to improve output stability and evidence attribution.
This technical overview presents a patent-pending control architecture for generative artificial intelligence based on structural state transitions, relation preservation, evidence attribution, structural stability evaluation, and selective verification. The proposed architecture treats generative AI processing as a sequence of structural state transitions and evaluates whether important relationships are preserved and whether generated information is adequately supported by available evidence. These distinct assessments are used to determine structural stability and to selectively trigger verification or generation-control operations, including re-reasoning, return to a preceding state, output modification, or output suppression. The technology is designed to be applicable to large language models, Retrieval-Augmented Generation (RAG), multimodal systems, agentic AI, question-answering systems, code-generation systems, and tool-using AI. This document is a public technical overview only. It does not disclose or replace the complete patent specification, specific evaluation functions, computational methods, parameters, threshold conditions, data structures, embodiments, or claims. Korean Patent Application No.: 10-2026-0150359Filing Date: 2026-08-11Inventor: Kyung Su KimStatus: Patent Pending
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