English(EN) SCAFFOLD: A Large-Scale Structured Dataset of Computer Science Research Figures with Diagram QA and Chain-of-Thought Reasoning Traces

新的SCAFFOLD数据集训练AI理解计算机科学研究图和图表

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员推出了SCAFFOLD，这是一个新颖的数据集，旨在训练视觉语言模型理解计算机科学研究论文中的复杂图表。该数据集包含来自arXiv论文的图像、标题、上下文信息、问题、答案和逐步推理轨迹。SCAFFOLD有多种尺寸，最大的版本SCAFFOLD-157K包含来自3000多篇论文的近157,000个问答对。初步实验使用了较小的SCAFFOLD-12K数据集和Qwen2.5-VL-3B-Instruct模型。 AI

影响支持开发能够理解科学文献中复杂视觉信息的AI模型。

排序理由该项目是一篇描述用于AI模型训练的新数据集的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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本文如何被排名

Signal score: 29 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该项目是一篇描述用于AI模型训练的新数据集的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Ranjit Raut, Aarav Subedi, Sagun Rai, Sudan Jha · 2026-09-02 04:00

SCAFFOLD：一个大规模结构化计算机科学研究图表数据集，包含图表问答和思维链推理轨迹

arXiv:2609.00018v1 Announce Type: new Abstract: Computer science papers rely heavily on diagrams: architecture drawings, system flowcharts, and pipeline schematics that often carry more information than the text around them. There is currently no public dataset that pairs this sp…

本文如何被排名

报道来源 [1]

SCAFFOLD：一个大规模结构化计算机科学研究图表数据集，包含图表问答和思维链推理轨迹

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