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Conference peer review constitutes a human-computation process whose importance cannot be overstated: not only it identifies the best submissions for acceptance, but, ultimately, it impacts the future of the whole research area by promoting some ideas and restraining others.
Avoiding a tragedy of the commons in the peer review process
Sculley, D., Snoek, J., and Wiltschko, A. B. (2019) · 1901
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Does my rebuttal matter? Insights from a major NLP conference
Gao, Y., Eger, S., Kuznetsov, I., Gurevych, I., and Miyao, Y. (2019) · 1903
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Probable inference, the law of succession, and statistical inference
Wilson, E. B. (1927) · 1927
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The design of experiments
Fisher, R. A. (1935) · 1935
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Design and analysis of the NIPS 2016 review process
Shah, N. B., Tabibian, B., Muandet, K., Guyon, I., and Von Luxburg, U. (2018) · 1946
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Author perception of peer review: impact of review quality and acceptance on satisfaction
Weber, E. J., Katz, P. P., Waeckerle, J. F., and Callaham, M. L. (2002) · 2002
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Experiences from the sigcomm 2005 european shadow pc experiment
Feldmann, A. (2005) · 2005
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Is peer review broken? submissions are up, reviewers are overtaxed, and authors are lodging complaint after complaint about the process at top-tier journals. what’s wrong with peer review?
McCook, A. (2006) · 2006
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Author feedback experiment at pam 2007
Papagiannaki, K. (2007) · 2007
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Hypercriticality
Vardi, M. Y. (2010) · 2010
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More than fun and money. worker motivation in crowdsourcing–a study on mechanical turk
Kaufmann, N., Schulze, T., and Veit, D. (2011) · 2011
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Analysis of reviews for CVPR 2012
Khosla, A., Hoiem, D., and Belongie, S. (2013) · 2012
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The effects of demand characteristics on research participant behaviours in non-laboratory settings: a systematic review
McCambridge, J., De Bruin, M., and Witton, J. (2012) · 2012
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Breaking monotony with meaning: Motivation in crowdsourcing markets
Chandler, D. and Kapelner, A. (2013) · 2013
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The Toronto Paper Matching System: An automated paper-reviewer assignment system
Charlin, L. and Zemel, R. S. (2013) · 2013
Cited alongside, same era.
Towards more constructive reviewing of SIGCOMM papers
Mogul, J. C. (2013) · 2013
Cited alongside, same era.
Impartial peer review
Kurokawa, D., Lev, O., Morgenstern, J., and Procaccia, A. D. (2015) · 2015
Cited alongside, same era.
Understanding over participation in simple contests
Levy, P. and Sarne, D. (2018) · 2018
Cited alongside, same era.
The conference paper assignment problem: Using order weighted averages to assign indivisible goods
Lian, J. W., Mattei, N., Noble, R., and Walsh, T. (2018) · 2018
Cited alongside, same era.
New reviewer mentoring program
Picciotto, M. (2018) · 2018
Cited alongside, same era.
What we learned from NeurIPS 2019 data
Beygelzimer, A., Fox, E., dÁlche Buc, F., and Larochelle, H. (2019) · 2020
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A SUPER* algorithm to optimize paper bidding in peer review
Fiez, T., Shah, N., and Ratliff, L. (2020) · 2020
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Diversifying peer review by adding junior scientists
Garisto, D. (2019) · 2020
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Mitigating manipulation in peer review via randomized reviewer assignments
Jecmen, S., Zhang, H., Liu, R., Shah, N. B., Conitzer, V., and Fang, F. (2020) · 2020
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Distributed peer review enhanced with natural language processing and machine learning
Kerzendorf, W. E., Patat, F., Bordelon, D., van de Ven, G., and Pritchard, T. A. (2020) · 2020
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Supporting robust, rigorous, and reliable reviewing as the cornerstone of our profession: Introducing a competency framework for peer review
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Stelmakh, I., Shah, N. B., and Singh, A. (2018) · 2018
Cited alongside, same era.
The Distributed Peer Review Experiment
Patat, F., Kerzendorf, W., Bordelon, D., Van de Ven, G., and Pritchard, T. (2019) · 2019
Cited alongside, same era.
Double decker peer review
Shah, N. (2019a) · 2019
Cited alongside, same era.
On testing for biases in peer review
Stelmakh, I., Shah, N., and Singh, A. (2019) · 2019
Cited alongside, same era.
Your 2 is my 1, your 3 is my 9: Handling arbitrary miscalibrations in ratings
Wang, J. and Shah, N. B. (2019) · 2019
Cited alongside, same era.
On strategyproof conference review
Xu, Y., Zhao, H., Shi, X., and Shah, N. (2019) · 2019
Cited alongside, same era.
Köhler, T., González-Morales, M. G., Banks, G. C., O’Boyle, E. H., Allen, J. A., Sinha, R., Woo, S. E., and Gulick, L. M. (2020) · 2020
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Hirepeer: Impartial peer-assessed hiring at scale in expert crowdsourcing markets
Kotturi, Y., Kahng, A., Procaccia, A. D., and Kulkarni, C. (2020) · 2020
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When the bubble bursts…
Langford, J. (2018) · 2020
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What we learned from NeurIPS 2020 reviewing process
Lin, H.-T., Balcan, M. F., Hadsell, R., and Ranzato, M. (2020) · 2020
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Loss functions, axioms, and peer review
Noothigattu, R., Shah, N. B., and Procaccia, A. D. (2020) · 2020
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Prior and prejudice: The novice reviewers’ bias against resubmissions in conference peer review
Stelmakh, I., Shah, N. B., Singh, A., and Daumé III, H. (2020) · 2020
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Getting involved in the peer review process
Tomiyama, A. J. (2007) · 2020
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Reading like a graduate student
Toor, R. (2009) · 2020
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