| Challenge: | Using early returns and venue, we can predict which papers will be highly cited in the future. |
| Approach: | They ask whether early returns are predictive of papers' citations . |
| Outcome: | The authors show early returns are more predictive than venue . early returns also predicts which papers will be highly cited in the future . |
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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. |
What Can We Do to Improve Peer Review in NLP? (2020.findings-emnlp)
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| 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. |
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Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers (2021.naacl-industry)
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| Challenge: | , . ; : () () . . |
| Approach: | cnn.com/industrietrack/reviewers.html#reviews.html #reviewer_list.html . |
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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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Retrieval of the Best Counterargument without Prior Topic Knowledge (P18-1)
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| Challenge: | ad-hominem attacks are the most common form of argumentation in real life . |
| Approach: | They hypothesize that the best counterargument invokes the same aspects as the argument while having the opposite stance. |
| Outcome: | The proposed model is independent from the topic at hand, i.e., it applies to arbitrary arguments. |
Findings of the Association for Computational Linguistics: EMNLP 2021 (2021.findings-emnlp)
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| Challenge: | . - (EN) |
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Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021.findings-acl)
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Findings of the Association for Computational Linguistics: EMNLP 2025 (2025.findings-emnlp)
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| Challenge: | null |
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Findings of the Association for Computational Linguistics: EMNLP 2020 (2020.findings-emnlp)
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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. |
| Approach: | They propose to use peer review to assess the effectiveness of rebuttal phase in NLP conferences. |
| Outcome: | The proposed task predicts after-rebuttal scores from initial reviews and author responses. |