system-one-models

TypedBench is a new benchmark for evaluating System One typed decision models on calibration, wording sensitivity, policy adherence, and decision cost under asymmetric cost matrices, comparing a hosted model, an open encoder, and open decoder families on identical items.

GraphDecisionBench：一个模型无关的基准，用于评估 System One 模型在图结构任务上的决策能力，涵盖 14 种模型-接口配置，揭示了邻接识别准确并不等同于结构正确性等关键发现。

This paper benchmarks typed 'System One' decision models against supervised classifiers and generative language models for automated decision gates, finding that model rankings depend on label availability, calibration, and cost. It introduces condition-dependent design rules and shows cascaded models can match accuracy at a fraction of the cost.