Datasets:
GEM
/

Tasks:
Other
Languages: English
Multilinguality: unknown
Size Categories: unknown
Language Creators: unknown
Annotations Creators: none
Source Datasets: original
License:
Sebastian Gehrmann commited on
Commit
c33560c
1 Parent(s): 833d627

Data Card.

Browse files
Files changed (2) hide show
  1. README.md +1 -1
  2. SciDuet.json +1 -1
README.md CHANGED
@@ -194,7 +194,7 @@ Training, validation and testing data contain 136, 55, and 81 papers from ACL An
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  <!-- info: Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g., if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here. -->
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  <!-- scope: microscope -->
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- The dataset integrated into GEM is the ACL portion of the whole dataset described in "https://aclanthology.org/2021.naacl-main.111.pdf", It contains the full Dev and Test sets, and a portion of the Train dataset.
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  Note that although we cannot release the whole training dataset due to copyright issues, researchers can still use our released data procurement code to generate the training dataset from the online ICML/NeurIPS anthologies.
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  <!-- info: Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g., if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here. -->
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  <!-- scope: microscope -->
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+ The dataset integrated into GEM is the ACL portion of the whole dataset described in the [paper](https://aclanthology.org/2021.naacl-main.111), It contains the full Dev and Test sets, and a portion of the Train dataset.
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  Note that although we cannot release the whole training dataset due to copyright issues, researchers can still use our released data procurement code to generate the training dataset from the online ICML/NeurIPS anthologies.
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SciDuet.json CHANGED
@@ -34,7 +34,7 @@
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  "structure": {
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  "structure-labels": "The original papers and slides (both are in PDF format) are carefully processed by a combination of PDF/Image processing tookits. The text contents from multiple slides that correspond to the same slide title are mreged.",
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  "structure-splits": "Training, validation and testing data contain 136, 55, and 81 papers from ACL Anthology and their corresponding slides, respectively. ",
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- "structure-splits-criteria": "The dataset integrated into GEM is the ACL portion of the whole dataset described in \"https://aclanthology.org/2021.naacl-main.111.pdf\", It contains the full Dev and Test sets, and a portion of the Train dataset. \nNote that although we cannot release the whole training dataset due to copyright issues, researchers can still use our released data procurement code to generate the training dataset from the online ICML/NeurIPS anthologies."
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  },
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  "what": {
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  "dataset": "This dataset supports the document-to-slide generation task where a model has to generate presentation slide content from the text of a document. "
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  "structure": {
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  "structure-labels": "The original papers and slides (both are in PDF format) are carefully processed by a combination of PDF/Image processing tookits. The text contents from multiple slides that correspond to the same slide title are mreged.",
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  "structure-splits": "Training, validation and testing data contain 136, 55, and 81 papers from ACL Anthology and their corresponding slides, respectively. ",
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+ "structure-splits-criteria": "The dataset integrated into GEM is the ACL portion of the whole dataset described in the [paper](https://aclanthology.org/2021.naacl-main.111), It contains the full Dev and Test sets, and a portion of the Train dataset. \nNote that although we cannot release the whole training dataset due to copyright issues, researchers can still use our released data procurement code to generate the training dataset from the online ICML/NeurIPS anthologies."
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  },
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  "what": {
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  "dataset": "This dataset supports the document-to-slide generation task where a model has to generate presentation slide content from the text of a document. "