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@@ -51,7 +51,6 @@ This dataset was created by modifying and adapting the [allenai/QASPER: a datase
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  and **aims to generate Question-Answer Pairs from the Abstract, Introduction of an NLP Paper**.
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- ## Dataset Details
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  ### Dataset Description
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@@ -62,15 +61,17 @@ and **aims to generate Question-Answer Pairs from the Abstract, Introduction of
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  - validation : 211 rows
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  - test : 320 rows
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-
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  - **Curated by:** [@UNIST-Eunchan](https://huggingface.co/UNIST-Eunchan)
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- ### Dataset Sources [optional]
 
 
 
 
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  <!-- Provide the basic links for the dataset. -->
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  - **Repository:** [allenai/qasper](https://huggingface.co/datasets/allenai/qasper)
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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  - **Question-based Summarization**
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  <!-- Address questions around how the dataset is intended to be used. -->
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- [More Information Needed]
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  ## Dataset Creation
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  ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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- [More Information Needed]
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- ### Source Data
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- This data is made by applying and processing [allenai/qasper](https://huggingface.co/datasets/allenai/qasper)
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
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  and **aims to generate Question-Answer Pairs from the Abstract, Introduction of an NLP Paper**.
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  ### Dataset Description
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  - validation : 211 rows
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  - test : 320 rows
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  - **Curated by:** [@UNIST-Eunchan](https://huggingface.co/UNIST-Eunchan)
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+
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+ -
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+ ### Dataset Sources
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+
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+ This data is made by applying and processing [allenai/qasper](https://huggingface.co/datasets/allenai/qasper)
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  <!-- Provide the basic links for the dataset. -->
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  - **Repository:** [allenai/qasper](https://huggingface.co/datasets/allenai/qasper)
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+
 
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  ## Uses
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  - **Question-based Summarization**
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  <!-- Address questions around how the dataset is intended to be used. -->
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  ## Dataset Creation
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  ### Curation Rationale
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+ Long Document Summarization datasets, especially those for Research Paper Summarization, are very limited and scarce.
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+ We tweak the existing data to provide domains and QA pairs specific to NLP among Research Papers.
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+ We expect to be able to generate multiple QA pairs if we let the model sample through training.
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+ We will release the fine-tuned model in the future.
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