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English(EN) METATR: A Multilingual, Evolving Benchmark for Automatic Text Recognition

新的METATR基准评估多语言ATR系统

研究人员推出了METATR(v1.0),一个旨在评估自动文本识别(ATR)系统,特别是视觉-大语言模型(vLLMs)的新型多语言基准。与专注于现代印刷英语文本的现有基准不同,METATR纳入了29种语言的各种文档,包含多种字体和版式。该基准包括一个标准化的提示和规范化方法,以及一个动态评估框架,以确保可重复性和可扩展性。初步评估显示,虽然专有模型通常表现更一致,但在不同字体和版式之间存在显著的性能差异。 AI

影响 为多语言ATR系统提供了一个更全面的评估框架,解决了当前基准的局限性。

排序理由 该集群描述了一个用于评估AI系统的新学术基准的发布。

在 arXiv cs.CV 阅读 →

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新的METATR基准评估多语言ATR系统

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Research
该集群描述了一个用于评估AI系统的新学术基准的发布。
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2 independent sources
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paper, other
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111 days old
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · M\'elodie Boillet, Sol\`ene Tarride, Christopher Kermorvant ·

    METATR:一个多语言、可演进的自动文本识别基准

    arXiv:2605.26712v1 Announce Type: new Abstract: Benchmarks that reflect the diversity and complexity of real-world documents are essential for accurately evaluating Automatic Text Recognition (ATR) systems, especially Vision-Large Language Models (vLLMs). Although recent models d…

  2. arXiv cs.CV TIER_1 English(EN) · Christopher Kermorvant ·

    METATR:一个多语言、可演进的自动文本识别基准

    Benchmarks that reflect the diversity and complexity of real-world documents are essential for accurately evaluating Automatic Text Recognition (ATR) systems, especially Vision-Large Language Models (vLLMs). Although recent models demonstrate impressive performance, they are ofte…