Fetching the paper…
Reading the bibliography…
We study a new problem setting of information extraction (IE), referred to as text-to-table.
Open information extraction from the web
Michele Banko, Michael J. Cafarella, Stephen Soderland, Matthew Broadhead, and Oren Etzioni. 2007 · 2007
Earlier work this paper cites.
Open information extraction using wikipedia
Fei Wu and Daniel S. Weld. 2010 · 2010
Earlier work this paper cites.
Open language learning for information extraction
Mausam, Michael Schmitz, Stephen Soderland, Robert Bart, and Oren Etzioni. 2012 · 2012
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Earlier work this paper cites.
Bidirectional lstm-crf models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
Earlier work this paper cites.
chrf: character n-gram f-score for automatic MT evaluation
Maja Popovic. 2015 · 2015
Earlier work this paper cites.
Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
Earlier work this paper cites.
Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
Earlier work this paper cites.
End-to-end sequence labeling via bi-directional lstm-cnns-crf
Xuezhe Ma and Eduard Hovy. 2016 · 2016
Earlier work this paper cites.
Creating training corpora for nlg micro-planning
Claire Gardent, Anastasia Shimorina, Shashi Narayan, and Laura Perez-Beltrachini. 2017 · 2017
Earlier work this paper cites.
The e2e dataset: New challenges for end-to-end generation
Jekaterina Novikova, Ondřej Dušek, and Verena Rieser. 2017 · 2017
Earlier work this paper cites.
Fast and accurate entity recognition with iterated dilated convolutions
Emma Strubell, Patrick Verga, David Belanger, and Andrew McCallum. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Challenges in data-to-document generation
Sam Wiseman, Stuart M Shieber, and Alexander M Rush. 2017 · 2017
Earlier work this paper cites.
Joint extraction of entities and relations based on a novel tagging scheme
Suncong Zheng, Feng Wang, Hongyun Bao, Yuexing Hao, Peng Zhou, and Bo Xu. 2017 · 2017
Earlier work this paper cites.
Table-to-text: Describing table region with natural language
Junwei Bao, Duyu Tang, Nan Duan, Zhao Yan, Yuanhua Lv, Ming Zhou, and Tiejun Zhao. 2018 · 2018
Earlier work this paper cites.
Learning to progressively recognize new named entities with sequence to sequence models
Lingzhen Chen and Alessandro Moschitti. 2018 · 2018
Earlier work this paper cites.
A deep ensemble model with slot alignment for sequence-to-sequence natural language generation
Juraj Juraska, Panagiotis Karagiannis, Kevin Bowden, and Marilyn Walker. 2018 · 2018
Earlier work this paper cites.
Table-to-text generation by structure-aware seq2seq learning
Tianyu Liu, Kexiang Wang, Lei Sha, Baobao Chang, and Zhifang Sui. 2018 · 2018
Cited alongside, same era.
An attention-based bilstm-crf approach to document-level chemical named entity recognition
Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Hongfei Lin, and Jian Wang. 2018 · 2018
Cited alongside, same era.
Deep graph convolutional encoders for structured data to text generation
Diego Marcheggiani and Laura Perez-Beltrachini. 2018 · 2018
Cited alongside, same era.
Supervised open information extraction
Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, and Ido Dagan. 2018 · 2018
Cited alongside, same era.
Improving clinical named entity recognition with global neural attention
Guohai Xu, Chengyu Wang, and Xiaofeng He. 2018 · 2018
Cited alongside, same era.
Extracting relational facts by an end-to-end neural model with copy mechanism
Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
Later among the works it cites.
Reasoning with latent structure refinement for document-level relation extraction
Guoshun Nan, Zhijiang Guo, Ivan Sekulic, and Wei Lu. 2020 · 2020
Later among the works it cites.
Effective modeling of encoder-decoder architecture for joint entity and relation extraction
Tapas Nayak and Hwee Tou Ng. 2020 · 2020
Later among the works it cites.
Totto: A controlled table-to-text generation dataset
Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, and Dipanjan Das. 2020 · 2020
Later among the works it cites.
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
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Xiangrong Zeng, Daojian Zeng, Shizhu He, Kang Liu, and Jun Zhao. 2018 · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Enhanced transformer model for data-to-text generation
Li Gong, Josep M Crego, and Jean Senellart. 2019 · 2019
Cited alongside, same era.
Text generation from knowledge graphs with graph transformers
Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, and Hannaneh Hajishirzi. 2019 · 2019
Cited alongside, same era.
A general framework for information extraction using dynamic span graphs
Yi Luan, Dave Wadden, Luheng He, Amy Shah, Mari Ostendorf, and Hannaneh Hajishirzi. 2019 · 2019
Cited alongside, same era.
Entity, relation, and event extraction with contextualized span representations
David Wadden, Ulme Wennberg, Yi Luan, and Hannaneh Hajishirzi. 2019 · 2019
Cited alongside, same era.
Docred: A large-scale document-level relation extraction dataset
Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, and Maosong Sun. 2019 · 2019
Cited alongside, same era.
Neural data-to-text generation via jointly learning the segmentation and correspondence
Xiaoyu Shen, Ernie Chang, Hui Su, Cheng Niu, and Dietrich Klakow. 2020 · 2020
Later among the works it cites.
Sportsett: Basketball-a robust and maintainable data-set for natural language generation
Craig Thomson, Ehud Reiter, and Somayajulu Sripada. 2020 · 2020
Later among the works it cites.
Span model for open information extraction on accurate corpus
Junlang Zhan and Hai Zhao. 2020 · 2020
Later among the works it cites.
Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Later among the works it cites.
GRIT: generative role-filler transformers for document-level event entity extraction
Xinya Du, Alexander M. Rush, and Claire Cardie. 2021 · 2021
Closest in time.
Document-level entity-based extraction as template generation
Kung-Hsiang Huang, Sam Tang, and Nanyun Peng. 2021 · 2021
Closest in time.
Document-level event argument extraction by conditional generation
Sha Li, Heng Ji, and Jiawei Han. 2021 · 2021
Closest in time.
Text2event: Controllable sequence-to-structure generation for end-to-end event extraction
Yaojie Lu, Hongyu Lin, Jin Xu, Xianpei Han, Jialong Tang, Annan Li, Le Sun, Meng Liao, and Shaoyi Chen. 2021 · 2021
Closest in time.
DART: open-domain structured data record to text generation
Linyong Nan, Dragomir R. Radev, Rui Zhang, Amrit Rau, Abhinand Sivaprasad, Chiachun Hsieh, Xiangru Tang, Aadit Vyas, Neha Verma, Pranav Krishna, Yangxiaokang Liu, Nadia Irwanto, Jessica Pan, Faiaz Rahman, Ahmad Zaidi, Mutethia Mutuma, Yasin Tarabar, Ankit Gupta, Tao Yu, Yi Chern Tan, Xi Victoria Lin, Caiming Xiong, Richard Socher, and Nazneen Fatema Rajani. 2021 · 2021
Closest in time.
Structured prediction as translation between augmented natural languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cícero Nogueira dos Santos, Bing Xiang, and Stefano Soatto. 2021 · 2021
Closest in time.
A unified generative framework for various NER subtasks
Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, and Xipeng Qiu. 2021 · 2021
Closest in time.
A frustratingly easy approach for entity and relation extraction
Zexuan Zhong and Danqi Chen. 2021 · 2021
Closest in time.
Data-to-text generation with entity modeling
Ratish Puduppully, Li Dong, and Mirella Lapata. 2019b · 2035
Closest in time.