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%0 Conference Proceedings
%T Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation
%A Wang, Peng
%A Lin, Junyang
%A Yang, An
%A Zhou, Chang
%A Zhang, Yichang
%A Zhou, Jingren
%A Yang, Hongxia
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F wang-etal-2021-sketch
%R 10.18653/v1/2021.findings-acl.427
%U https://aclanthology.org/2021.findings-acl.427
%U https://doi.org/10.18653/v1/2021.findings-acl.427
%P 4831-4843

Markdown (Informal)

[Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation](https://aclanthology.org/2021.findings-acl.427) (Wang et al., Findings 2021)

• Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation (Wang et al., Findings 2021)

ACL

• Peng Wang, Junyang Lin, An Yang, Chang Zhou, Yichang Zhang, Jingren Zhou, and Hongxia Yang. 2021. Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4831–4843, Online. Association for Computational Linguistics.