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English(EN) HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

新HIRA系统通过人机协同检索增强文档分类

研究人员开发了HIRA,一个专为受监管行业文档分类设计的新型系统。HIRA采用无需训练、本地部署的检索增强级联方法,结合了多种表示类型,包括OCR文本、密集嵌入和图像级数据。该系统通过检索优先处理置信度高的分类,将不确定的文档传递给本地托管的LLM验证器,仅在必要时升级到人工审查。这种方法显著提高了分类准确性,同时最大限度地减少了对广泛人工标注和LLM调用的需求。 AI

影响 该系统为受监管环境中文档分类的模型再训练提供了一个实用的替代方案,降低了成本并提高了准确性。

排序理由 该集群描述了一篇详细介绍新型文档分类系统的新研究论文。

在 arXiv cs.IR (Information Retrieval) 阅读 →

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新HIRA系统通过人机协同检索增强文档分类

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该集群描述了一篇详细介绍新型文档分类系统的新研究论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Shangxuan Tian, Yanhui Chen, Carlos Queiroz ·

    HIRA:受监管行业文档分类的闭环检索增强级联模型

    arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-governance procedures. We present HIRA, a training-free, on-premises retrieval-aug…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Carlos Queiroz ·

    HIRA:受监管行业文档分类的带人回环检索增强级联

    Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-governance procedures. We present HIRA, a training-free, on-premises retrieval-augmented cascade for document classification in re…