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The escalating volume of academic research, coupled with a shortage of qualified reviewers, necessitates innovative approaches to peer review.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Earlier work this paper cites.
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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Automated Machine Learning: Methods, Systems, Challenges
F. Hutter, L. Kotthoff, and J. Vanschoren. 2019 · 2019
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Deep learning in citation recommendation models survey
Zafar Ali, Pavlos Kefalas, Khan Muhammad, Bahadar Ali, and Muhammad Imran. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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AI-assisted peer review
Alessio Checco, Lorenzo Bracciale, Paola Loreti, Stephen Pinfield, and Giuseppe Bianchi. 2021 · 2021
Earlier work this paper cites.
Automl: A survey of the state-of-the-art
X. He, K. Zhao, and X. Chu. 2021 · 2021
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The quality assist: A technology-assisted peer review based on citation functions to predict the paper quality
Setio Basuki and Masatoshi Tsuchiya. 2022 · 2022
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The evolving crisis of the peer-review process
Maria Petrescu and Anjala S Krishen. 2022 · 2022
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Is the future of peer review automated?
Richard Schulz, Adrian Barnett, René Bernard, Nicholas J Brown, JA Byrne, Peter Eckmann, Marianna A Gazda, Halil Kilicoglu, Elisabeth M Prager, Michael Salholz-Hillel, and 1 others. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, and 1 others. 2023 · 2023
Cited alongside, same era.
Reviewergpt? an exploratory study on using large language models for paper reviewing
Ryan Liu and Nihar B Shah. 2023 · 2023
Cited alongside, same era.
Self-refine: Iterative refinement with self-feedback
Aman Madaan, Jason Tuck, Jayesh Gupta, Amir Yazdanbakhsh, Yash Zheng, Vivek Srikumar, Deepak Pathak, Denny Yang, Partha Talukdar, and Karan Goel. 2023 · 2023
Cited alongside, same era.
Ai in materials discovery
Marg: Multi-agent review generation for scientific papers (arxiv: 2401.04259). arxiv
M D’Arcy, T Hope, L Birnbaum, and D Downey. 2024 · 2024
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Simulating 500 million years of evolution with a language model
T. Hayes, R. Rao, H. Akin, and 1 others. 2024 · 2024
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Teaching language models to self-improve by learning from language feedback
Chi Hu, Yimin Hu, Hang Cao, Tong Xiao, and Jingbo Zhu. 2024 · 2024
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The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Rates
Giovanni R Latona, Manoel H Ribeiro, Thomas R Davidson, Vlad Veselovsky, and Robert West. 2024 · 2024
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The ai scientist: Towards fully automated open-ended scientific discovery
Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob Foerster, Jeff Clune, and David Ha. 2024 · 2024
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A. Merchant, E. Pyzer-Knapp, P. Szymanski, and 1 others. 2023 · 2023
Cited alongside, same era.
Gpt4 is slightly helpful for peer-review assistance: A pilot study
Zachary Robertson. 2023 · 2023
Cited alongside, same era.
Use of artificial intelligence and the future of peer review
Howard Bauchner and Frederick P Rivara. 2024 · 2024
Cited alongside, same era.
Ai-assisted academia: Navigating the nuances of peer review with chatgpt 4
Som S Biswas. 2024 · 2024
Cited alongside, same era.
PEERRec: An AI-based approach to automatically generate recommendations and predict decisions in peer review
Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, and Asif Ekbal
Cited in the paper.
Augmenting negative representation for continual self-supervised learning
Sungmin Cha, Kyunghyun Cho, and Taesup Moon
Cited in the paper.
Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Smith, Yian Yin, Daniel McFarland, and James Zou
Cited in the paper.
“statcheck”: Automatically detect statistical reporting inconsistencies to increase reproducibility of meta-analyses
Michèle B. Nuijten and Joshua R. Polanin
Cited in the paper.
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Llmrefine: Pinpointing and refining large language models via fine-grained actionable feedback
Wenda Xu, Daniel Deutsch, Mara Finkelstein, Juraj Juraska, Biao Zhang, Zhongtao Liu, William Yang Wang, Lei Li, and Markus Freitag. 2024 · 2024
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Is llm a reliable reviewer? a comprehensive evaluation of llm on automatic paper reviewing tasks
Ruiyang Zhou, Lu Chen, and Kai Yu. 2024 · 2024
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Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, Saizhuo Wang, Kun Zhang, Yuanzhuo Wang, Wen Gao, Lionel Ni, and Jian Guo. 2025 · 2025
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