arXiv cs.CY· Holly Baker, Michael Kuo, Kyana Pollas·· 13 小时前AI 评分31
Policy Central：检测警务政策中的冲突、冗余与相似性
Policy Central: Detecting Conflicts, Redundancy, and Similarity in Deployed Police Policy
AI 导读
Policy Central 是一个已部署系统，用于发现警察部门书面政策各条款之间的关系，区分冲突、冗余、相似与不同。
正文 · 原文
Abstract:Policy Central is a deployed system that helps police departments find relationships between sections of their written policy: whether two sections conflict, are redundant, are merely similar, or are different. We describe the system and compare two architectures. Retrieve-Judge, a retrieve-then-classify pipeline, runs as a cheap library-wide health signal; Screen-Confirm, a screen-then-confirm cascade, is a selective audit of the documents a reviewer chooses, checking them exhaustively against one another. On a 302-pair benchmark drawn from one department's ~84 real policy documents, given each pair Screen-Confirm reaches 0.795 aggregate recall and 0.885 on Conflict, so current models judge well. Finding the pair is the hard part: Retrieve-Judge's composed recall falls to 0.457, and Screen-Confirm recovers 0.472 (0.615 on Conflict). Today these pairs are found by reading the whole library, nearly 20,000 sections, checked against one another and re-checked after every revision. A scan that returns half of them in minutes, at low cost, and can be re-run on demand changes the economics of policy review even before recall improves.
| Comments: | 16 pages, 2 figures. Committed to EACL 2027 |
| Subjects: | Computation and Language (cs.CL); Computers and Society (cs.CY) |
| Cite as: | arXiv:2610.29338 [cs.CL] |
| (or arXiv:2610.29338v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.29338 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Holly Baker [view email]
[v1]
Wed, 21 Oct 2026 07:34:59 UTC (216 KB)
来源：arXiv cs.CY · arxiv.org