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Decision Model Factory: Building Specialized Sovereign Decision Models
Yuma Ichikawa

Decision Model Factory: Building Specialized Sovereign Decision Models

Author / Organization:
Computer Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

Decision needs vary with each application, language, and deployment environment. The Decision Model Factory turns those needs into specialized, sovereign models on demand. A brief recipe guides the training, calibration, verification, and evaluation of a selected backbone, delivering a deployable decision model under the operator's control. The same workflow creates a new specialist whenever the requirements change. Across Japanese decision tasks, compact deployment, and long-context passage ranking, five factory-built models improve upon their backbones; three surpass the strongest results in a fixed public Japanese benchmark comparison. A dedicated runner computes only permitted-answer probabilities and reuses shared context, more than doubling serving speed on matched multi-question workloads with essentially unchanged decision scores. Together, the factory and runner make fast, task-specific decision models practical to build and deploy whenever needed.

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Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title Decision Model Factory: Building Specialized Sovereign Decision Models
Author / Organization Yuma Ichikawa
Subject & Discipline cs.AI
Categories Computer Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-3654
Original Source Link Visit Source Page on arxiv.org »