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English(EN) Safety That Does Not Transfer: Cross-Lingual Clinical Correctness Drift in Deployable Medical Language Models

医疗AI模型在从英语切换到豪萨语时表现出显著的安全漂移

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新近发表在arXiv上的研究揭示，当从英语切换到豪萨语时，可部署的医疗语言模型在临床正确性方面出现了显著下降。研究人员发现，虽然一个前沿模型在豪萨语中保持了高准确率，但较小的、可在本地部署的模型性能却大幅下降，甚至产生了有害的响应。这种漂移在各种医疗条件下都有观察到，并归因于模型类别而非语言本身，这凸显了低资源医疗环境中AI跨语言安全性的关键差距。 AI

影响 强调了在低资源、多语言医疗环境中部署小型AI模型所面临的关键安全问题。

排序理由 学术论文，详细阐述了关于AI模型性能的研究发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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医疗AI模型在从英语切换到豪萨语时表现出显著的安全漂移

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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Anthonio Oladimeji Gabriel, Dimeji Olawuyi, Toba Ajayi, Temilola Aderemi ·

    无法转移的安全性：可部署医疗语言模型中的跨语言临床正确性漂移

    arXiv:2607.17270v1 Announce Type: new Abstract: Safety evaluation of large language models is conducted predominantly in English and predominantly on frontier systems. Neither condition describes how such models are encountered in low-resource health settings, where small quantis…

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