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arXivEdits: Understanding the Human Revision Process in Scientific Writing

Jiang, Chao, Xu, Wei, Stevens, Samuel·2022·Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
DOI 10.18653/v1/2022.emnlp-main.641
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  • More advanced processing of revisions has been approached for arXiv pre-prints and ACL publications, and in the context of peer review.

    “more advanced processing of revisions has been approached for arXiv pre-prints (Jiang et al., 2022; Du et al., 2022) and ACL publications (Mita et al., 2022), and in the context of peer review (Kuznetsov et al., 2022; D'Arcy et al., 2023).”

    From What Can Natural Language Processing Do for Peer Review? (2024) · cites this paper as Jiang et al., 2022

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Research works printed but not linked: 35

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  3. Shane Bergsma, Matt Post, and David Yarowsky. 2012. Stylometric analysis of scientific articles. In Pro- ceedings of the 2012 Conference of the North Amer- ican Chapter of the Association for Computational Linguistics: Human Language Technologies.
  4. Amit Bronner and Christof Monz. 2012. User edits classification using document revision histories. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Lin- guistics.
  5. Christopher Bryant, Mariano Felice, Øistein E. Ander- sen, and Ted Briscoe. 2019. The BEA-2019 shared task on grammatical error correction. In Proceed- ings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications.
  6. Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018. A discourse-aware attention model for abstractive summarization of long documents. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computa- tional Linguistics: Human Language Technologies.
  7. Vidas Daudaravicius, Rafael E. Banchs, Elena Volod- ina, and Courtney Napoles. 2016. A report on the au- tomatic evaluation of scientific writing shared task. In Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications.
  8. Johannes Daxenberger. 2016. The writing process in online mass collaboration: NLP-supported ap- proaches to analyzing collaborative revision and user interaction. Ph.D. Thesis.
  9. Johannes Daxenberger and Iryna Gurevych. 2013. Au- tomatically classifying edit categories in Wikipedia revisions. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Process- ing.
  10. Qingxiu Dong, Xiaojun Wan, and Yue Cao. 2021. ParaSCI: A large scientific paraphrase dataset for longer paraphrase generation. In Proceedings of the 16th Conference of the European Chapter of the As- sociation for Computational Linguistics.
  11. Yao Dou, Chao Jiang, and Wei Xu. 2022. Improv- ing large-scale paraphrase acquisition and genera- tion. In Proceedings of the 2022 Conference on Em- pirical Methods in Natural Language Processing.
  12. Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, and Dongyeop Kang. 2022. Understanding iterative revision from human- written text. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics.
  13. Felix Faltings, Michel Galley, Gerold Hintz, Chris Brockett, Chris Quirk, Jianfeng Gao, and Bill Dolan. 2021. Text editing by command. In Proceedings of the 2021 Conference of the North American Chap- ter of the Association for Computational Linguistics: Human Language Technologies.
  14. Manaal Faruqui, Ellie Pavlick, Ian Tenney, and Dipan- jan Das. 2018. WikiAtomicEdits: A multilingual corpus of Wikipedia edits for modeling language and discourse. In Proceedings of the 2018 Confer- ence on Empirical Methods in Natural Language Processing.
  15. Katja Filippova, Enrique Alfonseca, Carlos A. Col- menares, Lukasz Kaiser, and Oriol Vinyals. 2015. Sentence compression by deletion with LSTMs. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing.
  16. Jill Fitzgerald. 1987. Research on revision in writing. Review of educational research.
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  18. Vidur Joshi, Matthew Peters, and Mark Hopkins. 2018. Extending a parser to distant domains using a few dozen partially annotated examples. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics.
  19. Omid Kashefi, Tazin Afrin, Meghan Dale, Christopher Olshefski, Amanda Godley, Diane Litman, and Re- becca Hwa. 2022. Argrewrite v. 2: an annotated ar- gumentative revisions corpus. Language Resources and Evaluation. · DOI
  20. Kalpesh Krishna, John Wieting, and Mohit Iyyer. 2020. Reformulating unsupervised style transfer as para- phrase generation. In Proceedings of the 2020 Con- ference on Empirical Methods in Natural Language Processing.
  21. Wuwei Lan, Chao Jiang, and Wei Xu. 2021. Neural semi-Markov CRF for monolingual word alignment. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Lan- guage Processing.
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  28. Allen Roush and Arvind Balaji. 2020. DebateSum: A large-scale argument mining and summarization dataset. In Proceedings of the 7th Workshop on Ar- gument Mining.
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  30. Chenhao Tan and Lillian Lee. 2014. A corpus of sentence-level revisions in academic writing: A step towards understanding statement strength in commu- nication. In Proceedings of the 52nd Annual Meet- ing of the Association for Computational Linguis- tics.
  31. Wei Xu, Chris Callison-Burch, and Courtney Napoles. 2015. Problems in current text simplification re- search: New data can help. Transactions of the As- sociation for Computational Linguistics.
  32. Wei Xu, Alan Ritter, Bill Dolan, Ralph Grishman, and Colin Cherry. 2012. Paraphrasing for style. In Pro- ceedings of COLING 2012.
  33. Huichao Xue and Rebecca Hwa. 2014. Redundancy de- tection in ESL writings. In Proceedings of the 14th Conference of the European Chapter of the Associa- tion for Computational Linguistics.
  34. Diyi Yang, Aaron Halfaker, Robert Kraut, and Eduard Hovy. 2017. Identifying semantic edit intentions from revisions in Wikipedia. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.
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Cited by

Sorted by citations

Authors
Jiang, C., Xu, W., & Stevens, S.
Venue
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
Published
2022
Pages
9420-9435
DOI
10.18653/v1/2022.emnlp-main.641
Cited by
9
References
5

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