OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering

OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering Zhengbao Jiang author Yi Mao author Pengcheng He author Graham Neubig author Weizhu Chen author 2022-07 text Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Marine Carpuat editor Marie-Catherine de Marneffe editor Ivan Vladimir Meza Ruiz editor Association for Computational Linguistics Seattle, United States conference publication jiang-etal-2022-omnitab 10.18653/v1/2022.naacl-main.68 https://aclanthology.org/2022.naacl-main.68/ 2022-07 932 942