QTSumm Dataset

The QTSumm dataset is a large-scale dataset for the task of query-focused summarization over tabular data. It contains 7,111 human-annotated query-summary pairs over 2,934 tables covering diverse topics. To solve this task, a text generation system has to perform human-like reasoning and analysis over the given table to generate a tailored summary.

Citation

@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 Ruizhe Chen and Xiangru Tang and Yumo Xu and Arman Cohan and Dragomir Radev},
      year={2023},
      eprint={2305.14303},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}