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ChatGPT, a large-scale language model based on the advanced GPT-3.5 architecture, has shown remarkable potential in various Natural Language Processing (NLP) tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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A new dataset and method for automatically grading ESOL texts
Helen Yannakoudakis, Ted Briscoe, and Ben Medlock. 2011 · 2011
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Better evaluation for grammatical error correction
Daniel Dahlmeier and Hwee Tou Ng. 2012 · 2012
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The MERLIN corpus: Learner language and the CEFR
Adriane Boyd, Jirka Hana, Lionel Nicolas, Detmar Meurers, Katrin Wisniewski, Andrea Abel, Karin Schöne, Barbora Štindlová, and Chiara Vettori. 2014 · 2014
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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
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How far are we from fully automatic high quality grammatical error correction?
Christopher Bryant and Hwee Tou Ng. 2015 · 2015
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Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault. 2016 · 2016
Earlier work this paper cites.
Automatic annotation and evaluation of error types for grammatical error correction
Christopher Bryant, Mariano Felice, and Ted Briscoe. 2017 · 2017
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JFLEG: A fluency corpus and benchmark for grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Overview of the nlpcc 2018 shared task: Grammatical error correction
Yuanyuan Zhao, Nan Jiang, Weiwei Sun, and Xiaojun Wan. 2018 · 2018
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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.
Cross-sentence grammatical error correction
Shamil Chollampatt, Weiqi Wang, and Hwee Tou Ng. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Cited alongside, same era.
Stronger baselines for grammatical error correction using a pretrained encoder-decoder model
Satoru Katsumata and Mamoru Komachi. 2020 · 2020
Cited alongside, same era.
GECToR – grammatical error correction: Tag, not rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub, and Oleksandr Skurzhanskyi. 2020 · 2020
Cited alongside, same era.
A simple recipe for multilingual grammatical error correction
Sascha Rothe, Jonathan Mallinson, Eric Malmi, Sebastian Krause, and Aliaksei Severyn. 2021 · 2021
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung. 2023 · 2023
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An analysis of gpt-3’s performance in grammatical error correction
Steven Coyne and Keisuke Sakaguchi. 2023 · 2023
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How good are gpt models at machine translation? a comprehensive evaluation
Amr Hendy, Mohamed Abdelrehim, Amr Sharaf, Vikas Raunak, Mohamed Gabr, Hitokazu Matsushita, Young Jin Kim, Mohamed Afify, and Hany Hassan Awadalla. 2023 · 2023
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Is chatgpt a good translator? yes with gpt-4 as the engine
Wenxiang Jiao, Wenxuan Wang, Jen tse Huang, Xing Wang, and Zhaopeng Tu. 2023 · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Cited alongside, same era.
Synthetic data generation for grammatical error correction with tagged corruption models
Felix Stahlberg and Shankar Kumar. 2021 · 2021
Cited alongside, same era.
Document-level grammatical error correction
Zheng Yuan and Christopher Bryant. 2021 · 2021
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Cited alongside, same era.
Prompting palm for translation: Assessing strategies and performance
David Vilar, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, and George Foster. 2022 · 2022
Cited alongside, same era.
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2023 · 2023
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A comprehensive evaluation of chatgpt’s zero-shot text-to-sql capability
Aiwei Liu, Xuming Hu, Lijie Wen, and Philip S. Yu. 2023 · 2023
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Chatgpt as a factual inconsistency evaluator for abstractive text summarization
Zheheng Luo, Qianqian Xie, and Sophia Ananiadou. 2023 · 2023
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Towards making the most of chatgpt for machine translation
Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, and Dacheng Tao. 2023 · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023 · 2023
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Chatgpt or grammarly? evaluating chatgpt on grammatical error correction benchmark
Haoran Wu, Wenxuan Wang, Yuxuan Wan, Wenxiang Jiao, and Michael Lyu. 2023 · 2023
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Exploring the limits of chatgpt for query or aspect-based text summarization
Xianjun Yang, Yan Li, Xinlu Zhang, Haifeng Chen, and Wei Cheng. 2023 · 2023
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