What Can We Do to Improve Peer Review in NLP?
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- What CanWe Do to Improve Peer Review in NLP
Final published version, 312 KB, PDF document
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.
|Title of host publication||Findings of the Association for Computational Linguistics: EMNLP 2020|
|Publisher||Association for Computational Linguistics|
|Publication status||Published - 2020|
|Event||The 2020 Conference on Empirical Methods in Natural Language Processing - online|
Duration: 16 Nov 2020 → 20 Nov 2020
|Conference||The 2020 Conference on Empirical Methods in Natural Language Processing|
|Periode||16/11/2020 → 20/11/2020|
Number of downloads are based on statistics from Google Scholar and www.ku.dk
No data available