English(EN) InsClaimBench: Benchmarking Insurance Claim Adjudication Across the Decision Chain

新基准揭示大型语言模型在保险理赔裁决方面存在困难

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-08 04:00

一项名为InsClaimBench的新基准测试已被开发出来，用于评估大型语言模型在保险理赔裁决方面的性能。该基准测试包含汽车、财产和健康保险的3,780个案例，评估模型连接证据、规则、判决和赔付计算的能力。对六个大型语言模型的评估显示，在决策链中可靠性有所下降，赔付决策准确率在74.23%到80.19%之间，而联合决策金额准确率则降至47.54%到73.15%。研究强调，尽管模型在单个规则上可能表现良好，但它们在整个裁决过程中一致地传播信息方面存在困难。 AI

影响凸显了当前大型语言模型在复杂、多步骤决策任务中的局限性，表明需要改进推理和一致性。

排序理由该项目是一篇研究论文，介绍了一个用于评估大型语言模型在特定任务上表现的新基准。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Linqi Zhang, Chong Qi, Yan Cheng, Wanqing Cao, Yu Liu, Chenwei Lin, Xian Xu · 2026-10-08 04:00

InsClaimBench：跨越决策链的保险理赔裁决基准测试

arXiv:2610.09671v1 Announce Type: new Abstract: Recent advances in reasoning-oriented large language models (LLMs) have motivated increasing evaluation of their ability to perform professional decision tasks. Insurance claim adjudication is one such task, requiring models to conn…

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InsClaimBench：跨越决策链的保险理赔裁决基准测试

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