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受治理数据分析：确定性策略执行优于运行时工具规划
原标题：MasterControl Seventeen Every Time
AI 摘要
arXiv 论文提出一种受治理的数据分析架构，其中语言模型仅负责解释用户问题，而确定性策略选择预编写的分析程序，确保结果附带完整证据。作者通过构造性翻译证明了该受限语言在特定分析类别上的完备性，并对比了运行时工具规划与策略执行两种方式：在440次运行中，策略执行在110次全部达标，而运行时规划在330次中无一满足完整契约。该结果具有配置特定性，不构成对智能体方法的普遍否定。
以上摘要由 AI 生成，可能存在误差。事实请以原文为准。
正文节选
From Question to Evidence: A Small Analytical Algebra for Governed Data Analysis Expressiveness, Deterministic Policy Execution, and a Controlled Comparison with Runtime Tool Planning Abstract A factual analyzer should not invent a new measuring method each time it answers a question. The difficulty is not generating a number; it is preserving what the number means: the population, time interval, measure, definitions, and supporting records. We study a simple architecture for bounded, read-only
发布时间：2026-09-05 12:00
抓取时间：2026-09-04 12:02
来源机构：arXiv