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English(EN) Reading Order Inference for Complex Document Layouts

新框架增强了复杂文档的阅读顺序推断能力

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新颖的、无需训练的框架，用于推断复杂文档布局中的阅读顺序，这对于数字化历史手稿尤其有益。这种基于图的方法将 OCR 文本行视为节点，并使用语言模型信号（如条件似然和 BERT 的下一句预测）对过渡进行评分。为了减轻级联错误，它采用了最大遗憾推断规则，优先考虑高机会成本的承诺。该方法在处理 Glossa Ordinaria 的挑战性布局时，在后继边准确率上显著优于 XY-cut 和 LayoutReader 等现有技术，达到 95%，在 OmniDocBench 的多栏子集上达到 88%。 AI

影响 提高了文档数字化准确性，尤其是在处理布局复杂的历史文本时。

排序理由 该项目是一篇学术论文，详细介绍了一种新的文档布局分析方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架增强了复杂文档的阅读顺序推断能力

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该项目是一篇学术论文，详细介绍了一种新的文档布局分析方法。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Iddo Hakim, Sharva Gogawale, Omer Ventura, Gal Grudka, Daria Vasyutinsky-Shapira, Berat Kurar-Barakat, Nachum Dershowitz ·

    复杂文档布局的阅读顺序推断

    arXiv:2607.01018v1 Announce Type: cross Abstract: Reading order inference remains a critical bottleneck in the digitization of complex historical manuscripts, where pages contain multiple spatially interleaved reading streams, the canonical example being the Glossa Ordinaria layo…

  2. arXiv cs.AI TIER_1 English(EN) · Nachum Dershowitz ·

    复杂文档布局的阅读顺序推断

    Reading order inference remains a critical bottleneck in the digitization of complex historical manuscripts, where pages contain multiple spatially interleaved reading streams, the canonical example being the Glossa Ordinaria layout, in which a central text is surrounded by comme…

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