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Grammatical Error Correction (GEC) has been broadly applied in automatic correction and proofreading system recently.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Better evaluation for grammatical error correction
Daniel Dahlmeier and Hwee Tou Ng. 2012 · 2012
Earlier work this paper cites.
Building a large annotated corpus of learner english: The nus corpus of learner english
Daniel Dahlmeier, Hwee Tou Ng, and Siew Mei Wu. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
The conll-2014 shared task on grammatical error correction
Hwee Tou Ng, Siew Mei Wu, Ted Briscoe, Christian Hadiwinoto, Raymond Hendy Susanto, and Christopher Bryant. 2014 · 2014
Earlier work this paper cites.
How far are we from fully automatic high quality grammatical error correction?
Christopher Bryant and Hwee Tou Ng. 2015 · 2015
Earlier work this paper cites.
Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015 · 2015
Earlier work this paper cites.
Reassessing the goals of grammatical error correction: Fluency instead of grammaticality
Keisuke Sakaguchi, Courtney Napoles, Matt Post, and Joel Tetreault. 2016 · 2016
Earlier work this paper cites.
Grammatical error correction using neural machine translation
Zheng Yuan and Ted Briscoe. 2016 · 2016
Earlier work this paper cites.
Jfleg: A fluency corpus and benchmark for grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault. 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.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Earlier work this paper cites.
Youdao’s winning solution to the nlpcc-2018 task 2 challenge: a neural machine translation approach to chinese grammatical error correction
Kai Fu, Jin Huang, and Yitao Duan. 2018 · 2018
Cited alongside, same era.
Overview of nlptea-2018 share task chinese grammatical error diagnosis
Gaoqi Rao, Qi Gong, Baolin Zhang, and Endong Xun. 2018 · 2018
Cited alongside, same era.
Overview of the nlpcc 2018 shared task: Grammatical error correction
Yuanyuan Zhao, Nan Jiang, Weiwei Sun, and Xiaojun Wan. 2018 · 2018
Cited alongside, same era.
Parallel iterative edit models for local sequence transduction
Abhijeet Awasthi, Sunita Sarawagi, Rasna Goyal, Sabyasachi Ghosh, and Vihari Piratla. 2019 · 2019
Cited alongside, same era.
The bea-2019 shared task on grammatical error correction
Christopher Bryant, Mariano Felice, Øistein E Andersen, and Ted Briscoe. 2019 · 2019
Cited alongside, same era.
Encoder-decoder models can benefit from pre-trained masked language models in grammatical error correction
Masahiro Kaneko, Masato Mita, Shun Kiyono, Jun Suzuki, and Kentaro Inui. 2020 · 2020
Later among the works it cites.
Felix: Flexible text editing through tagging and insertion
Jonathan Mallinson, Aliaksei Severyn, Eric Malmi, and Guillermo Garrido. 2020 · 2020
Later among the works it cites.
Gector–grammatical error correction: tag, not rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub, and Oleksandr Skurzhanskyi. 2020 · 2020
Later among the works it cites.
Overview of nlptea-2020 shared task for chinese grammatical error diagnosis
Gaoqi Rao, Erhong Yang, and Baolin Zhang. 2020 · 2020
Later among the works it cites.
Improving grammatical error correction with data augmentation by editing latent representation
Zhaohong Wan, Xiaojun Wan, and Wenguang Wang. 2020 · 2020
Later among the works it cites.
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
Encode, tag, realize: High-precision text editing
Eric Malmi, Sebastian Krause, Sascha Rothe, Daniil Mirylenka, and Aliaksei Severyn. 2019 · 2019
Cited alongside, same era.
Grammar error correction in morphologically rich languages: The case of russian
Alla Rozovskaya and Dan Roth. 2019 · 2019
Cited alongside, same era.
Improving grammatical error correction with machine translation pairs
Wangchunshu Zhou, Tao Ge, Chang Mu, Ke Xu, Furu Wei, and Ming Zhou. 2019 · 2019
Cited alongside, same era.
Revisiting pre-trained models for chinese natural language processing
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, and Guoping Hu. 2020 · 2020
Cited alongside, same era.
Grammatical error correction in low error density domains: A new benchmark and analyses
Simon Flachs, Ophélie Lacroix, Helen Yannakoudakis, Marek Rei, and Anders Søgaard. 2020 · 2020
Cited alongside, same era.
Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2019a
Cited in the paper.
Maskgec: improving neural grammatical error correction via dynamic masking
Zewei Zhao and Houfeng Wang. 2020 · 2020
Later among the works it cites.
Pre-training with whole word masking for chinese bert
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, and Ziqing Yang. 2021 · 2021
Later among the works it cites.
Cpt: A pre-trained unbalanced transformer for both chinese language understanding and generation
Yunfan Shao, Zhichao Geng, Yitao Liu, Junqi Dai, Fei Yang, Li Zhe, Hujun Bao, and Xipeng Qiu. 2021 · 2021
Later among the works it cites.
New dataset and strong baselines for the grammatical error correction of russian
Viet Anh Trinh and Alla Rozovskaya. 2021 · 2021
Later among the works it cites.
Ensembling and knowledge distilling of large sequence taggers for grammatical error correction
Maksym Tarnavskyi, Artem Chernodub, and Kostiantyn Omelianchuk. 2022 · 2022
Closest in time.
Mucgec: a multi-reference multi-source evaluation dataset for chinese grammatical error correction
Yue Zhang, Zhenghua Li, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, and Min Zhang. 2022 · 2022
Closest in time.