Encoder-Decoder Models Can Benefit from Pre-trained Masked Language
Models in Grammatical Error Correction

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Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction

3 May 2020

Masahiro Kaneko

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Papers citing "Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction"

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Title
Few-Shot Domain Adaptation for Grammatical Error Correction via Meta-Learning Shengsheng Zhang Yaping Huang Yun-Nung Chen Liner Yang Chencheng Wang Erhong Yang VLM 92 2 0 29 Jan 2021
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning Xuebo Liu Longyue Wang Derek F. Wong Liang Ding Lidia S. Chao Zhaopeng Tu AI4CE 66 35 0 29 Dec 2020
Chinese Grammatical Correction Using BERT-based Pre-trained Model Hongfei Wang Michiki Kurosawa Satoru Katsumata Mamoru Komachi 56 12 0 04 Nov 2020
Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction M. Chen Tao Ge Xingxing Zhang Furu Wei M. Zhou 89 47 0 07 Oct 2020
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction Masato Mita Shun Kiyono Masahiro Kaneko Jun Suzuki Kentaro Inui 70 14 0 07 Oct 2020
Adversarial Grammatical Error Correction Vipul Raheja Dimitrios Alikaniotis 70 11 0 06 Oct 2020
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling Mina Naghshnejad Tarun Joshi V. Nair VLM 48 6 0 04 Sep 2020