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Table Understanding

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TUTA is a unified pretrained model for understanding generally structured tables.

Based on TUTA, ForTaP further endows the model with stronger numerical-reasoning skills by pretraining on spreadsheet formulas.

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Code and Usages

Detailed implementations and usages of the pretrain models are shown in their folders:

Citation

If you find TUTA and ForTaP useful in your research, please consider citing following papers:

@inproceedings{wang2021tuta,
  title={TUTA: Tree-based Transformers for Generally Structured Table Pre-training},
  author={Wang, Zhiruo and Dong, Haoyu and Jia, Ran and Li, Jia and Fu, Zhiyi and Han, Shi and Zhang, Dongmei},
  booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
  pages={1780--1790},
  year={2021}
}
@article{cheng2021fortap,
  title={FORTAP: Using Formulae for Numerical-Reasoning-Aware Table Pretraining},
  author={Cheng, Zhoujun and Dong, Haoyu and Cheng, Fan and Jia, Ran and Wu, Pengfei and Han, Shi and Zhang, Dongmei},
  journal={arXiv preprint arXiv:2109.07323},
  year={2021}
}

Contact

If you have any problems regarding the paper or code, please feel free to submit issues in this repository. Or you can reach us by emails.

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