Tapex Large Finetuned Qtsumm

🚀 QTSumm Dataset

A query-focused table summarization dataset proposed in EMNLP 2023 for table-to-text, summarization, and long-form question-answering tasks.

🚀 Quick Start

The QTSumm dataset is a query-focused table summarization dataset introduced in the EMNLP 2023 paper QTSUMM: Query-Focused Summarization over Tabular Data. You can access the original Github repository here.

✨ Features

• Tags: table-to-text, summarization, long-form-question-answering
• Datasets: yale-nlp/QTSumm

📚 Documentation

Model Description

The model yale-nlp/tapex-large-finetuned-qtsumm (based on BART architecture) is initialized with microsoft/tapex-large and finetuned on the QTSumm dataset.

Usage

For more details on usage, please check the github repository: https://github.com/yale-nlp/QTSumm.

📄 License

This project is under the MIT license.

📖 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}
}