MasterControl Seventeen Every Time

论文概要

研究领域: AI/ML 作者: MasterControl AI Lab 发布时间: 2026-09-06 arXiv: 2509.00002

中文摘要

我们研究了一种受治理的企业分析方法：语言模型负责解释问题，而确定性策略选择并运行预先批准的分析程序，返回结果和证据。我们表明，这种限制在定义的分析类别内仍能保持表达能力，使用关系操作以及聚合、比较、窗口、排序和相似性操作。固定的语义、策略、数据和执行规则也使结果可重放。在440次运行中，三个8B模型在运行时生成SQL并选择工具，而Qwen3-8B仅解释意图，策略执行批准的程序。在330个运行时规划片段中，没有一个能在所有测试数据集上匹配完整的答案和证据契约；而策略执行的分析器在110次中匹配了110次。这是特定配置的结果，并不证明运行时智能体在其他设计下不能成功。

原文摘要

We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approved analytical program that returns both results and evidence. We show that this restriction can remain expressive within a defined analytical class, using relational operations plus aggregation, comparison, windows, ranking, and similarity. Fixed meaning, policy, data, and execution rules also make results replayable. Across 440 runs, three 8B models generated SQL and selected tools at runtime, while Qwen3-8B interpreted intent only and policy executed the approved program. None of 330 runtime-planning episodes matched the full answer-and-evidence contract across all test datasets; the policy-executed analyzer matched 110 of 110. This is a ...

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