@inproceedings{sakaguchi-etal-2017-grammatical,
title = "Grammatical Error Correction with Neural Reinforcement Learning",
author = "Sakaguchi, Keisuke and
Post, Matt and
Van Durme, Benjamin",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2062",
pages = "366--372",
abstract = "We propose a neural encoder-decoder model with reinforcement learning (NRL) for grammatical error correction (GEC). Unlike conventional maximum likelihood estimation (MLE), the model directly optimizes towards an objective that considers a sentence-level, task-specific evaluation metric, avoiding the exposure bias issue in MLE. We demonstrate that NRL outperforms MLE both in human and automated evaluation metrics, achieving the state-of-the-art on a fluency-oriented GEC corpus.",
}
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%0 Conference Proceedings
%T Grammatical Error Correction with Neural Reinforcement Learning
%A Sakaguchi, Keisuke
%A Post, Matt
%A Van Durme, Benjamin
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F sakaguchi-etal-2017-grammatical
%X We propose a neural encoder-decoder model with reinforcement learning (NRL) for grammatical error correction (GEC). Unlike conventional maximum likelihood estimation (MLE), the model directly optimizes towards an objective that considers a sentence-level, task-specific evaluation metric, avoiding the exposure bias issue in MLE. We demonstrate that NRL outperforms MLE both in human and automated evaluation metrics, achieving the state-of-the-art on a fluency-oriented GEC corpus.
%U https://aclanthology.org/I17-2062
%P 366-372
Markdown (Informal)
[Grammatical Error Correction with Neural Reinforcement Learning](https://aclanthology.org/I17-2062) (Sakaguchi et al., IJCNLP 2017)
ACL
- Keisuke Sakaguchi, Matt Post, and Benjamin Van Durme. 2017. Grammatical Error Correction with Neural Reinforcement Learning. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 366–372, Taipei, Taiwan. Asian Federation of Natural Language Processing.