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English(EN) FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures

FigEx2框架提取和标注科学图表数据

研究人员开发了FigEx2,一个新颖的框架,旨在从科学复合图中提取和标注信息。该系统解决了图表缺乏字幕的问题,而现有流程通常会忽略这些图表。FigEx2利用视觉条件化来联合生成面板特定的边界框和描述性文本,通过实体注意力KL正则化器和面板级别的实体F1奖励来提高定位和科学准确性。该框架在其精心策划的BioSci-Fig-Cap数据集上表现强劲,在字幕生成方面优于MedICaT数据集上的现有模型,并且还展示了对不同科学领域的零样本迁移能力。 AI

影响 通过实现复杂图表的自动化提取和字幕生成,增强了科学文献的可访问性和实用性。

排序理由 该集群包含一篇研究论文,详细介绍了处理科学图表的新框架和方法。 [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 1 个来源。 我们如何撰写摘要 →

FigEx2框架提取和标注科学图表数据

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Tool
该集群包含一篇研究论文,详细介绍了处理科学图表的新框架和方法。 [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) · Jifeng Song, Arun Das, Pan Wang, Hui Ji, Kun Zhao, Yufei Huang ·

    FigEx2:用于科学复合图的视觉条件面板检测与字幕生成

    arXiv:2601.08026v5 Announce Type: replace-cross Abstract: Scientific compound figures combine multiple labeled panels into a single image, and downstream pretraining and retrieval require panel-aligned visual-text pairs. However, in a PubMed Central (PMC)-scale crawl of 346,567 c…