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English(EN) Pre-Inference Routing for Cost-Efficient Document Field Extraction

新的路由系统通过预测难度来降低文档提取成本

研究人员开发了一种预推理路由系统,通过在处理前预测文档难度来优化文档字段提取。该方法使用廉价的、基于文档的信号来选择更便宜的提取模型和更强大的提取模型。该系统在退化的广告购买表单上展示了显著的成本降低,高达77%,同时将提取质量保持在接近始终使用更强大模型的水平。这种路由策略的有效性取决于更便宜的模型是否足够频繁地失败,以及这些失败是否可以从图像质量和布局等可见特征中预测出来。 AI

影响 这种路由方法可以显著降低处理大量不同文档的企业的运营成本。

排序理由 该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的文档字段提取方法。

在 arXiv cs.CL 阅读 →

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

新的路由系统通过预测难度来降低文档提取成本

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该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的文档字段提取方法。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Sreerekha Rajendran ·

    面向成本效益文档字段提取的预推理路由

    arXiv:2608.06607v1 Announce Type: new Abstract: Most document-extraction systems use a single model for all documents. This is simple but can be costly for easy cases and less effective for difficult ones. We examine whether we can predict a document's difficulty before extractio…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Sreerekha Rajendran ·

    面向成本高效文档字段提取的预推理路由

    Most document-extraction systems use a single model for all documents. This is simple but can be costly for easy cases and less effective for difficult ones. We examine whether we can predict a document's difficulty before extraction using inexpensive, document-based signals, and…