Datasets:
Tasks:
Summarization
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Update README.md
Browse files
README.md
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@@ -20,4 +20,20 @@ peersum_val = peersum_all.filter(lambda s: s['label'] == 'val')
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peersum_test = peersum_all.filter(lambda s: s['label'] == 'test')
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```
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You can also download the raw data from [Google Drive](https://drive.google.com/drive/folders/1SGYvxY1vOZF2MpDn3B-apdWHCIfpN2uB?usp=sharing). The raw data comprises more information and it can be used for other analysis for peer reviews.
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peersum_test = peersum_all.filter(lambda s: s['label'] == 'test')
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```
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The Huggingface dataset is mainly for multi-document summarization. Each sample comprises information with the following keys:
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```
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* paper_id: str (a link to the raw data)
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* paper_title: str
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* paper_abstract, str
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* paper_acceptance, str
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* meta_review, str
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* review_ids, list(str)
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* review_writers, list(str)
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* review_contents, list(str)
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* review_ratings, list(int)
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* review_confidences, list(int)
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* review_reply_tos, list(str)
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* label, str, (train, val, test)
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```
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You can also download the raw data from [Google Drive](https://drive.google.com/drive/folders/1SGYvxY1vOZF2MpDn3B-apdWHCIfpN2uB?usp=sharing). The raw data comprises more information and it can be used for other analysis for peer reviews.
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