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AI2D-RST: a multimodal corpus of 1000 primary school science diagrams
<span title="2020-12-05">2020</span>
<i title="Springer Science and Business Media LLC">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qiptgj2ubngu3hrrsrkbdvpchi" style="color: black;">Language Resources and Evaluation</a>
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AbstractThis article introduces AI2D-RST, a multimodal corpus of 1000 English-language diagrams that represent topics in primary school natural sciences, such as food webs, life cycles, moon phases and ...
Building on the segmentation of diagram layouts in AI2D, the AI2D-RST corpus presents a new multi-layer annotation schema that provides a rich description of their multimodal structure. ...
corpus of 1000 primary school science diagrams 2. ...
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AI2D-RST: A multimodal corpus of 1000 primary school science diagrams
[article]
<span title="2020-03-20">2020</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
This article introduces AI2D-RST, a multimodal corpus of 1000 English-language diagrams that represent topics in primary school natural sciences, such as food webs, life cycles, moon phases and human physiology ...
Building on the segmentation of diagram layouts in AI2D, the AI2D-RST corpus presents a new multi-layer annotation schema that provides a rich description of their multimodal structure. ...
In this article, we make a novel contribution to the study of diagrams by presenting AI2D-RST, a corpus of 1000 English-language diagrams that represent topics in primary school natural sciences. ...
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<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1912.03879v2">arXiv:1912.03879v2</a>
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Classifying Diagrams and Their Parts using Graph Neural Networks: A Comparison of Crowd-Sourced and Expert Annotations
[article]
<span title="2019-12-05">2019</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
This article compares two multimodal resources that consist of diagrams which describe topics in elementary school natural sciences. ...
This article reports on two experiments that evaluate how effectively crowd-sourced and expert-annotated graphs can represent the multimodal structure of diagrams for representation learning using various ...
Here the aim is to evaluate to what extent graph neural networks can learn about the generic structure of primary school science diagrams from the graph-based representations in AI2D and AI2D-RST. ...
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<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1912.02866v1">arXiv:1912.02866v1</a>
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Semiotically-grounded distant viewing of diagrams: insights from two multimodal corpora
[article]
<span title="2021-03-08">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
In this article, we bring together theories of multimodal communication and computational methods to study how primary school science diagrams combine multiple expressive resources. ...
diagrams as a mode of communication. ...
The AI2D-RST corpus covers 1000 diagrams from AI2D. ...
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<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.04692v1">arXiv:2103.04692v1</a>
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