T5 Large Finetuned Qtsumm

🚀 QTSumm Dataset

QTSumm is a query - focused table summarization dataset. It addresses the need for effective tabular data summarization based on specific queries. This dataset was proposed in the EMNLP 2023 paper QTSUMM: Query - Focused Summarization over Tabular Data. The original Github repository can be found at https://github.com/yale-nlp/QTSumm.

✨ Features

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

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

Basic Usage

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

📚 Documentation

Model Description

yale-nlp/t5-large-finetuned-qtsumm (based on T5 architecture) is initialized with t5-large and finetuned on the QTSumm dataset.

📄 License

This project is licensed 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}
}