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Reviewing Natural Language Processing Research


This tutorial will cover the goals, processes, and evaluation of reviewing research in natural language processing. As has been pointed out for years by leading figures in our community (Web-ber, 2007), researchers in the ACL community face a heavy-and growing-reviewing burden. Initiatives to lower this burden have been discussed at the recent ACL general assembly in Florence (ACL 2019) 1. Simultaneously, notable "false negatives"-rejection by our conferences of work that was later shown to be tremendously important after acceptance by other conferences (Church, 2005)-has raised awareness of the fact that our reviewing practices leave something to be desired.. . and we do not often talk about "false positives" with respect to conference papers, but conversations in the hallways at *ACL meetings suggest that we have a publication bias towards papers that report high performance, with perhaps not much else of interest in them (Manning, 2015). It need not be this way. There is good reason to think that reviewing is a learnable (and teachable).
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hal-02943568 , version 1 (21-09-2020)



Kevin Bretonnel Cohen, Karën Fort, Margot Mieskes, Aurélie Névéol. Reviewing Natural Language Processing Research. Annual Meeting of the Association for Computational Linguistics (ACL), Jul 2020, Seattle, United States. pp.16 - 18, ⟨10.18653/v1/2020.acl-tutorials.4⟩. ⟨hal-02943568⟩
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