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--- |
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dataset_info: |
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features: |
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- name: article_id |
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dtype: string |
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- name: abstract_text |
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dtype: string |
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- name: token_count |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 150590869 |
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num_examples: 140313 |
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|
- name: test |
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num_bytes: 5848235 |
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num_examples: 5481 |
|
|
- name: val |
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|
num_bytes: 5748332 |
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num_examples: 5383 |
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download_size: 90308446 |
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dataset_size: 162187436 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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|
- split: val |
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path: data/val-* |
|
|
--- |
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# arXiv Abstract |
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This dataset is based on the arXiv scientific papers and is used for the text expansion task. ([Download raw data here](https://drive.google.com/file/d/1b3rmCSIoh6VhD4HKWjI4HOW-cSwcwbeC/view?usp=sharing)). |
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I processed the raw data for the article expansion task with `extract_arXiv_abstract.py`. The processed dataset only contains the article ID and abstract fields, and the abstract length should be 100-300 tokens. The JSON objects are in the following format: |
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``` |
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{ |
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'article_id': str, |
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'abstract_text': List[str], |
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'token_count': int |
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} |
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|