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Table Understanding

This is the official repository of:

• TUTA:Tree-based Transformers for Generally Structured Table Pre-training
• ForTaP:Using Formulae for Numerical-Reasoning-Aware Table Pretraining.

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.

:beers: News

• 2024-11-12: “Encoding Spreadsheets for Large Language Models” at EMNLP 2024.

• 2024-7-15: A tutorial on “Large Language Models for Tabular Data” at SIGIR 2024.

• 2022-7-23: A survey on “Table Pretraining: A Survey on Model Architectures, Pretraining Objectives, and Downstream Tasks” at IJCAI 2022.

• 2022-03-22: We released ForTaP code.

• 2022-03-08: ForTaP was accepted by ACL 2022. You may find ForTaP paper here.

• 2022-01-09: We updated cell type classification code for TUTA.

• 2021-10-29: We released TUTA code.

• 2021-9-2: We released HiTab, a large dataset on question answering and data-to-text over complex hierarchical tables.

• 2021-8-17: TUTA was accepted by KDD 2021.

• 2020-10-21: We released our TUTA paper on arXiv.

Code and Usages

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

• TUTA
• ForTaP

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.

Contributing

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Trademarks

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