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Evaluation of text generation to date has primarily focused on content created sequentially, rather than improvements on a piece of text.
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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Easse: Easier automatic sentence simplification evaluation
Fernando Alva-Manchego, Louis Martin, Carolina Scarton, and Lucia Specia. 2019 · 1908
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Encode, tag, realize: High-precision text editing
Eric Malmi, Sebastian Krause, Sascha Rothe, Daniil Mirylenka, and Aliaksei Severyn. 2019 · 1909
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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The writing process and process writing
Anthony Seow. 2002 · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Muss: multilingual unsupervised sentence simplification by mining paraphrases
Louis Martin, Angela Fan, Éric de la Clergerie, Antoine Bordes, and Benoît Sagot. 2020 · 2005
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Microsoft research at duc 2006: task-focused summarization with sentence simplification and lexical expansion
Lucy Vanderwende, Hisami Suzuki, and Chris Brockett. 2006 · 2006
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When the editor disappears, does editing disappear?
Susan Greenberg. 2010 · 2010
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Identifying semantic edit intentions from revisions in wikipedia
Diyi Yang, Aaron Halfaker, Robert Kraut, and Eduard Hovy. 2017 · 2010
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A monolingual tree-based translation model for sentence simplification
Zhemin Zhu, Delphine Bernhard, and Iryna Gurevych. 2010 · 2010
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Joint learning of a dual smt system for paraphrase generation
Hong Sun and Ming Zhou. 2012 · 2012
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The impact of iterative writing and feedback on the characteristics of tertiary students’ written texts
Iris Vardi. 2012 · 2012
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An analysis of crowdsourced text simplifications
Marcelo Adriano Amancio and Lucia Specia. 2014 · 2014
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Predicting grammaticality on an ordinal scale
Michael Heilman, Aoife Cahill, Nitin Madnani, Melissa Lopez, Matthew Mulholland, and Joel R. Tetreault. 2014 · 2014
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Aligning sentences from standard wikipedia to simple wikipedia
William Hwang, Hannaneh Hajishirzi, Mari Ostendorf, and Wei Wu. 2015 · 2015
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Ground truth for grammatical error correction metrics
Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault. 2015 · 2015
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A deeper exploration of the standard pb-smt approach to text simplification and its evaluation
Sanja Štajner, Hannah Béchara, and Horacio Saggion. 2015 · 2015
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Problems in current text simplification research: New data can help
Wei Xu, Chris Callison-Burch, and Courtney Napoles. 2015 · 2015
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A redundancy-aware sentence regression framework for extractive summarization
Pengjie Ren, Furu Wei, Zhumin Chen, Jun Ma, and Ming Zhou. 2016 · 2016
Cited alongside, same era.
Optimizing statistical machine translation for text simplification
Wei Xu, Courtney Napoles, Ellie Pavlick, Quanze Chen, and Chris Callison-Burch. 2016 · 2016
Cited alongside, same era.
Grammatical error correction using neural machine translation
Zheng Yuan and Ted Briscoe. 2016 · 2016
Cited alongside, same era.
Semeval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
Cited alongside, same era.
Jfleg: A fluency corpus and benchmark for grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault. 2017 · 2017
Cited alongside, same era.
Exploring neural text simplification models
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. 2019 · 2019
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Asset: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations
Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, and Lucia Specia. 2020 · 2020
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wikihowtoimprove: A resource and analyses on edits in instructional texts
Talita Anthonio, Irshad Bhat, and Michael Roth. 2020 · 2020
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Automatically neutralizing subjective bias in text
Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, and Diyi Yang. 2020 · 2020
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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, Peter J Liu, et al. 2020 · 2020
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, and Liviu P Dinu. 2017 · 2017
Cited alongside, same era.
A corpus of annotated revisions for studying argumentative writing
Fan Zhang, Homa B Hashemi, Rebecca Hwa, and Diane Litman. 2017 · 2017
Cited alongside, same era.
A multilayer convolutional encoder-decoder neural network for grammatical error correction
Shamil Chollampatt and Hwee Tou Ng. 2018 · 2018
Cited alongside, same era.
Reaching human-level performance in automatic grammatical error correction: An empirical study
Tao Ge, Furu Wei, and Ming Zhou. 2018 · 2018
Cited alongside, same era.
Sentence-level fluency evaluation: references help, but can be spared!
Katharina Kann, Sascha Rothe, and Katja Filippova. 2018 · 2018
Cited alongside, same era.
The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. 2018 · 2018
Cited alongside, same era.
Multi-reward reinforced summarization with saliency and entailment
Ramakanth Pasunuru and Mohit Bansal. 2018 · 2018
Cited alongside, same era.
Parasci: A large scientific paraphrase dataset for longer paraphrase generation
Qingxiu Dong, Xiaojun Wan, and Yue Cao. 2021 · 2021
Later among the works it cites.
The GEM benchmark: Natural language generation, its evaluation and metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Anuoluwapo Aremu, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna-Adriana Clinciu, Dipanjan Das, Kaustubh Dhole, Wanyu Du, Esin Durmus, Ondřej Dušek, Chris Chinenye Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Mihir Kale, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Andre Niyongabo Rubungo, Salomey Osei, Ankur Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, and Jiawei Zhou. 2021 · 2021
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Fruit: Faithfully reflecting updated information in text
Robert L Logan IV, Alexandre Passos, Sameer Singh, and Ming-Wei Chang. 2021 · 2021
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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Understanding iterative revision from human-written text
Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, and Dongyeop Kang. 2022 · 2022
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The advantage of an iterative writing process for novels and short stories
Annie Jackson. 2022 · 2022
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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, et al. 2022 · 2022
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Improving wikipedia verifiability with ai
Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, and Sebastian Riedel. 2022 · 2022
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, and Alexander M Rush. 2022 · 2022
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Peer: A collaborative language model
Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, and Sebastian Riedel. 2022 · 2022
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Newsedits: A news article revision dataset and a novel document-level reasoning challenge
Alexander Spangher, Xiang Ren, Jonathan May, and Nanyun Peng. 2022 · 2022
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Benchmarking generalization via in-context instructions on 1,600+ language tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, et al. 2022 · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer. 2022 · 2022
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