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English(EN) Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner

新的基准和工具链增强视觉大语言模型进行表格识别

研究人员开发了一个新的基准和框架,以提高视觉大语言模型(VLLMs)识别非结构化表格的能力。研究发现低质量的图像输入是一个主要障碍。为解决此问题,他们引入了邻居引导工具链推理器(NGTR),它使用各种轻量级工具来提高图像质量并指导工具选择过程。实验表明,NGTR显著提升了VLLMs在表格识别任务中的性能。 AI

影响 这项研究可以改进AI模型处理和理解表格数据的方式,可能影响数据分析和信息提取。

排序理由 该集群包含一篇学术论文,详细介绍了用于AI研究的新基准和框架。[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 1 个来源。 我们如何撰写摘要 →

新的基准和工具链增强视觉大语言模型进行表格识别

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该集群包含一篇学术论文,详细介绍了用于AI研究的新基准和框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yitong Zhou, Mingyue Cheng, Qingyang Mao, Jiahao Wang, Feiyang Xu, Xin Li ·

    利用视觉大语言模型增强表格识别:基准测试与邻域引导工具链推理器

    arXiv:2412.20662v4 Announce Type: replace-cross Abstract: Pre-trained foundation models have recently made significant progress in table-related tasks such as table understanding and reasoning. However, recognizing the structure and content of unstructured tables using Vision Lar…