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Peer review constitutes a core component of scholarly publishing; yet it demands substantial expertise and training, and is susceptible to errors and biases.
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, et al. 2020 · 1901
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Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Scientific peer review
Lutz Bornmann. 2011 · 2011
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Bias in peer review
Carole J. Lee, Cassidy R. Sugimoto, Guo Zhang, and Blaise Cronin. 2013 · 2013
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Emerging trends in peer review—a survey
Richard Walker and Pascal Rocha da Silva. 2015 · 2015
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What to do about non-standard (or non-canonical) language in NLP
Barbara Plank. 2016 · 2016
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Computational support for academic peer review: A perspective from artificial intelligence
Simon Price and Peter A Flach. 2017 · 2017
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Reviewer bias in single- versus double-blind peer review
Andrew Tomkins, Min Zhang, and William D. Heavlin. 2017 · 2017
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The STM Report: An overview of scientific and scholarly publishing
Rob Johnson, Anthony Watkinson, and Michael Mabe. 2018 · 2018
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A dataset of peer reviews (PeerRead): Collection, insights and NLP applications
Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, and Roy Schwartz. 2018 · 2018
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Scibert: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
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DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions
Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, and Pushpak Bhattacharyya. 2019 · 2019
Cited alongside, same era.
Argument mining for understanding peer reviews
Xinyu Hua, Mitko Nikolov, Nikhil Badugu, and Lu Wang. 2019 · 2019
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Your 2 is my 1, your 3 is my 9: Handling arbitrary miscalibrations in ratings
Jingyan Wang and Nihar B. Shah. 2019 · 2019
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APE: Argument pair extraction from peer review and rebuttal via multi-task learning
Liying Cheng, Lidong Bing, Qian Yu, Wei Lu, and Luo Si. 2020 · 2020
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
Cited alongside, same era.
What can we do to improve peer review in NLP?
Efficient hierarchical domain adaptation for pretrained language models
Alexandra Chronopoulou, Matthew Peters, and Jesse Dodge. 2022 · 2022
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Yes-yes-yes: Proactive data collection for ACL rolling review and beyond
Nils Dycke, Ilia Kuznetsov, and Iryna Gurevych. 2022 · 2022
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DEMix layers: Disentangling domains for modular language modeling
Suchin Gururangan, Mike Lewis, Ari Holtzman, Noah A. Smith, and Luke Zettlemoyer. 2022 · 2022
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DISAPERE: A dataset for discourse structure in peer review discussions
Neha Kennard, Tim O’Gorman, Rajarshi Das, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Hamed Zamani, and Andrew McCallum. 2022 · 2022
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Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review
Ilia Kuznetsov, Jan Buchmann, Max Eichler, and Iryna Gurevych. 2022 · 2022
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Anna Rogers and Isabelle Augenstein. 2020 · 2020
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Uncertainty-aware machine support for paper reviewing on the interspeech 2019 submission corpus
Lukas Stappen, Georgios Rizos, Madina Hasan, Thomas Hain, and Björn W. Schuller. 2020 · 2020
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Assisting decision making in scholarly peer review: A preference learning perspective
Nils Dycke, Edwin Simpson, Ilia Kuznetsov, and Iryna Gurevych. 2021 · 2021
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On the stability of fine-tuning BERT: misconceptions, explanations, and strong baselines
Marius Mosbach, Maksym Andriushchenko, and Dietrich Klakow. 2021 · 2021
Cited alongside, same era.
Prior and prejudice: The novice reviewers’ bias against resubmissions in conference peer review
Ivan Stelmakh, Nihar B Shah, Aarti Singh, and Hal Daumé III. 2021 · 2021
Cited alongside, same era.
Unsupervised domain adaptation with adapter
Rongsheng Zhang, Yinhe Zheng, Xiaoxi Mao, and Minlie Huang. 2021 · 2021
Cited alongside, same era.
Peer review analyze: A novel benchmark resource for computational analysis of peer reviews
Tirthankar Ghosal, Sandeep Kumar, Prabhat Kumar Bharti, and Asif Ekbal. 2022a
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Chenglei Qin and Chengzhi Zhang. 2022 · 2022
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Principled Methods to Improve Peer Review
Nihar B Shah. 2019 · 2022
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MReD: A meta-review dataset for structure-controllable text generation
Chenhui Shen, Liying Cheng, Ran Zhou, Lidong Bing, Yang You, and Luo Si. 2022 · 2022
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Can we automate scientific reviewing?
Weizhe Yuan, Pengfei Liu, and Graham Neubig. 2022 · 2022
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Scim: Intelligent skimming support for scientific papers
Raymond Fok, Hita Kambhamettu, Luca Soldaini, Jonathan Bragg, Kyle Lo, Marti Hearst, Andrew Head, and Daniel S Weld. 2023 · 2023
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