Decision Model Factory: Building Specialized Sovereign Decision Models
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.
Authors
- Yuma Ichikawa (ORCID: https://orcid.org/0009-0004-4216-7017)
Publication Details
- Journal
- arXiv (Cornell University)
- Published
- 2026-10-26
- DOI
- https://doi.org/10.48550/arxiv.2610.34956
- Primary Topic
- Topic Modeling
- Type
- preprint