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English(EN) Broad and Efficient PII Detection with Unified Labels

新的PII检测器以更低的成本实现高召回率 · arXiv研究

研究人员开发了一种新的PII检测模型,该模型既广泛又高效,解决了现有检测器通常依赖复杂架构和有限合成数据集的局限性。该新模型在77个公共数据集的百万个以上示例上进行训练,并在统一定义下重新标记,与较大的基线相比,在AI4Privacy和Nemotron-PII等关键基准上实现了更高的召回率。值得注意的是,它以显著更低的计算成本实现了这一点,吞吐量提高了2-10倍,并且所需的GPU内存大大减少。 AI

影响 该模型可以显著降低大规模数据处理中PII检测的成本并提高其有效性。

排序理由 该集群包含一篇详细介绍新模型及其在基准测试上评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新的PII检测器以更低的成本实现高召回率 · arXiv研究

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该集群包含一篇详细介绍新模型及其在基准测试上评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Andy Hsu, Konstantin Berlin ·

    使用统一标签进行广泛而高效的PII检测

    arXiv:2610.22597v1 Announce Type: new Abstract: Personally Identifiable Information (PII) detection models must efficiently find identifiers across diverse contexts while maintaining a low false-positive rate (FPR) on high-volume traffic. Recent detectors increasingly rely on com…