Skip to content
English

Switch theme

arXiv 2610.28522 · cs.AI · 2026-10-20

DecisionPivot: A Diagnostic Benchmark for Decision Models in LLM Systems

Xialie Zhuang, Mingcong Lei, Zunhai Su, Ri Liu, Jianjin Li, Peixian Ma, Jia Pan, Ngai Wong and 2 more

StartLux

In latest · #92 Added on 2026-10-24

One-line takeaway

DecisionPivot diagnoses decision models used for routing, guardrails and verification in LLM systems: 48 tasks, 40,033 items, 7 roles, with contrast groups testing correctness under controlled variations. Across 40 decision and 14 general models, two 27B models 2.6 points apart on the reference track score 70.1% vs 44.2% on contrast groups.

DecisionPivot 是给 LLM 系统里的“判定模型”(路由、护栏、输出校验)做诊断的基准:48 个任务、40,033 题、7 种判定角色,核心轨用对照组检验模型在细节变化下是否判对。评测 40 个判定模型和 14 个通用模型发现:两个参考轨只差 2.6 分的 27B 模型,对照组准确率分别是 70.1% 和 44.2%。

74HF upvotes
148GitHub stars
1Citations (Semantic Scholar)
60.5Buzz score

Read on arXiv PDF Hugging Face discussion Code

About this data

Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.

The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.

Data updated: Latest AI papers(UTC+8)