| Challenge: | Traditionally, peer review is expected to act as a filter for high-quality, impactful work, but this does not hold in practice. |
| Approach: | They argue that peer review is becoming increasingly spurious and that it is a problem for NLP . they propose a reproducibility checklist at EMNLP 2020 that could be used to ensure that papers are reproducible. |
| Outcome: | The reproducibility checklist at EMNLP 2020 is the first step in that direction. |
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| Challenge: | a survey of the NLP community shows that paper-reviewer matching is a problem . authors lose valuable time and opportunities by writing reviews that are arbitrarily low . |
| Approach: | They propose to use paper-reviewer matching to improve peer review . they identify common issues and perspectives on what factors should be considered . |
| Outcome: | The proposed method improves the quality of peer review and improves interpretable peer review assignments. |
Program Chairs’ Report on Peer Review at ACL 2023 (2023.acl-long)
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| Challenge: | ACL'23 makes its peer review report public and an official part of the conference proceedings. |
| Approach: | They present an analysis of the factors affecting peer review and identify the most problematic issues that the authors complained about. |
| Outcome: | The authors identified the most problematic issues and provided suggestions for the future chairs. |
Reviewing Natural Language Processing Research (2021.eacl-tutorials)
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| Challenge: | a tutorial on reviewing is a useful tool for researchers who are new to the field of NLP. |
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Does My Rebuttal Matter? Insights from a Major NLP Conference (N19-1)
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| Challenge: | Peer review is a core element of the scientific process, but few studies have evaluated its properties empirically. |
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NLPeer: A Unified Resource for the Computational Study of Peer Review (2023.acl-long)
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| Challenge: | Existing studies of peer review for scholarly publications lack datasets and multi-domain corpora to support this complex process. |
| Approach: | They propose to use NLPeer to build a multi-domain corpus of more than 5k papers and 11k review reports from five different venues to support reviewers. |
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Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future (2026.acl-long)
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Sihong Wu, Owen Jiang, Yilun Zhao, Tiansheng Hu, Yiling Ma, Kaiyan Zhang, Manasi Patwardhan, Arman Cohan
| Challenge: | Recent advances in large language models (LLMs) motivated methods that assist or automate different stages of peer review pipeline. |
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Reviewing Natural Language Processing Research (2020.acl-tutorials)
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| Challenge: | a tutorial on reviewing research in natural language processing will cover the theory and practice of reviewing research. |
| Approach: | tutorial covers the theory and practice of reviewing research in natural language processing . authors say reviewers should be more aware of "false negatives" |
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Is NLP Ready for Standardization? (2022.findings-emnlp)
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| Challenge: | a number of scientific fields, including telecommunications, networks and multimedia, lack standards in the field of NLP. |
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Autonomous Machine Learning-Based Peer Reviewer Selection System (2025.coling-demos)
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| Challenge: | Existing systems that match papers with experts are inefficient and often require long turnaround times. |
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A Systematic Review of Reproducibility Research in Natural Language Processing (2021.eacl-main)
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| Challenge: | Despite the recent progress in reproducibility, the field is far from reaching a consensus on how reproducibility should be defined, measured and addressed. |
| Approach: | They propose to provide a wide-angle snapshot of current work on reproducibility in NLP. |
| Outcome: | The proposed work will provide a wide-angle snapshot of current work on reproducibility in NLP. |