arXiv Open Access 2020

What Can We Do to Improve Peer Review in NLP?

Anna Rogers Isabelle Augenstein

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Abstrak

Peer review is our best tool for judging the quality of conference submissions, but it is becoming increasingly spurious. We argue that a part of the problem is that the reviewers and area chairs face a poorly defined task forcing apples-to-oranges comparisons. There are several potential ways forward, but the key difficulty is creating the incentives and mechanisms for their consistent implementation in the NLP community.

Topik & Kata Kunci

cs.CL cs.AI

Penulis (2)

Anna Rogers

Isabelle Augenstein

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APA MLA BibTeX

Rogers, A., Augenstein, I. (2020). What Can We Do to Improve Peer Review in NLP?. https://arxiv.org/abs/2010.03863

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓