QTSumm Dataset

QTSumm is a query-focused table summarization dataset proposed in EMNLP 2023 paper QTSUMM: Query-Focused Summarization over Tabular Data. The original Github repository is https://github.com/yale-nlp/QTSumm.

Model Description

yale-nlp/bart-large-finetuned-qtsumm (based on BART architecture) is initialized with facebook/bart-large and finetuned on the QTSumm dataset.

Usage

Check the github repository: https://github.com/yale-nlp/QTSumm

Reference

@misc{zhao2023qtsumm,
      title={QTSUMM: Query-Focused Summarization over Tabular Data}, 
      author={Yilun Zhao and Zhenting Qi and Linyong Nan and Boyu Mi and Yixin Liu and Weijin Zou and Simeng Han and Xiangru Tang and Yumo Xu and Arman Cohan and Dragomir Radev},
      year={2023},
      eprint={2305.14303},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
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Dataset used to train yale-nlp/bart-large-finetuned-qtsumm