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English(EN) KhatianDoc: A Human-Verified Benchmark Diagnosing Multimodal LLM Failure on Bengali Legal Land Records

新基准揭示多模态大语言模型在孟加拉语法律土地记录上存在失败

一个名为 KhatianDoc 的新基准已被开发出来,用于评估多模态大语言模型(LLMs)在理解孟加拉语法律土地记录方面的能力。该基准由孟加拉国的 107 份真实土地记录构建而成,包含符号识别、十六进制到十进制转换、结构化字段提取和问答等任务。对六个大语言模型的评估显示存在重大失败,模型无法正确回答近 40% 的问题,并且在涉及土地所有权分数的算术任务上表现不如基线。 AI

影响 突显了多模态大语言模型在理解专业、非拉丁字母脚本数据方面的关键差距,表明需要进行领域特定的训练和评估。

排序理由 学术论文,介绍了一个用于评估大语言模型在特定领域能力的新基准。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新基准揭示多模态大语言模型在孟加拉语法律土地记录上存在失败

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学术论文,介绍了一个用于评估大语言模型在特定领域能力的新基准。[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) · Tasmiad Hasan, Arafat Zaman Ratul, Sarker Sadman Saalim, S. M. Shah Nawaz Hossain, Khan Raiyan Ibne Reza, Sumaiya Tabassum Nimi ·

    KhatianDoc:一个经人类验证的基准,诊断多模态大语言模型在孟加拉国法律土地记录上的失败

    arXiv:2609.03597v1 Announce Type: new Abstract: Land ownership in Bangladesh is recorded in Ana-Ganda-Kora-Kranti-Til, a base-16 positional fraction system with dedicated Unicode glyphs, no mainstream font, and no coverage in any OCR pipeline or tokenizer. The handwritten records…