You Can Generate It Again: Data-to-Text Generation with Verification and Correction Prompting

A Hierarchical Model for Data-to-Text Generation

Original

Clément Rebuffel, Laure Soulier, Geoffrey Scoutheeten, and Patrick Gallinari. 2019 · 1912

Earlier work this paper cites.

Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics . 311–318

Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002

Earlier work this paper cites.

ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out . Association for Computational Linguistics, Barcelona, Spain, 74–81

Chin-Yew Lin. 2004 · 2004

Earlier work this paper cites.

METEOR: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments. In Proceedings of the Second Workshop on Statistical Machine Translation . Association for Computational Linguistics, Prague, Czech Republic, 228–231

Alon Lavie and Abhaya Agarwal. 2007 · 2007

Earlier work this paper cites.

CIDEr: Consensus-based Image Description Evaluation

Original

Ramakrishna Vedantam, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015

Earlier work this paper cites.

The E2E Dataset: New Challenges For End-to-End Generation. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue . Association for Computational Linguistics, Saarbrücken, Germany, 201–206

Jekaterina Novikova, Ondřej Dušek, and Verena Rieser. 2017 · 2017

Earlier work this paper cites.

ViGGO: A Video Game Corpus for Data-To-Text Generation in Open-Domain Conversation. In Proceedings of the 12th International Conference on Natural Language Generation . Association for Computational Linguistics, Tokyo, Japan

Juraj Juraska, Kevin Bowden, and Marilyn Walker. 2019 · 2019

Earlier work this paper cites.

Data-to-text generation with content selection and planning. In Proceedings of the AAAI conference on artificial intelligence , Vol. 33. 6908–6915

Ratish Puduppully, Li Dong, and Mirella Lapata. 2019 · 2019

Earlier work this paper cites.

Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity. In Proceedings of the 28th International Conference on Computational Linguistics . International Committee on Computational Linguistics, Barcelona, Spain (Online)

Hamza Harkous, Isabel Groves, and Amir Saffari. 2020 · 2020

Earlier work this paper cites.

Template guided text generation for task-oriented dialogue

Original

Mihir Kale and Abhinav Rastogi. 2020 · 2020

Cited alongside, same era.

Controllable Meaning Representation to Text Generation: Linearization and Data Augmentation Strategies. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Association for Computational Linguistics, Online, 5160–5185

Chris Kedzie and Kathleen McKeown. 2020 · 2020

Cited alongside, same era.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020

Cited alongside, same era.

Attention Is Indeed All You Need: Semantically Attention-Guided Decoding for Data-to-Text NLG. In Proceedings of the 14th International Conference on Natural Language Generation . Association for Computational Linguistics, Aberdeen, Scotland, UK, 416–431

Juraj Juraska and Marilyn Walker. 2021 · 2021

Cited alongside, same era.

P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) . Association for Computational Linguistics, Dublin, Ireland, 61–68

Xiao Liu, Kaixuan Ji, Yicheng Fu, Weng Tam, Zhengxiao Du, Zhilin Yang, and Jie Tang. 2022 · 2022

Later among the works it cites.

Improving Compositional Generalization with Self-Training for Data-to-Text Generation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Dublin, Ireland

Sanket Vaibhav Mehta, Jinfeng Rao, Yi Tay, Mihir Kale, Ankur Parikh, and Emma Strubell. 2022 · 2022

Later among the works it cites.

How Do Seq2Seq Models Perform on End-to-End Data-to-Text Generation?. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, Dublin, Ireland, 7701–7710

Xunjian Yin and Xiaojun Wan. 2022 · 2022

Later among the works it cites.