--- title: "Who cites Can We Automate Scientific — 69 citing papers" description: "69 papers of the Elamur Research library cite «Can We Automate Scientific Reviewing?», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Can We Automate Scientific Reviewing?](https://md.research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/) / cited by # Who cites «Can We Automate Scientific Reviewing?» 69 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «Can We Automate Scientific Reviewing?»](https://md.research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/) 1. **[Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,423 citations* 2. [**BARTScore: Evaluating Generated Text as Text Generation arXiv:2106.11520**Weizhe Yuan, Graham Neubig, Pengfei Liu*2021 · 815 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/) 3. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models arXiv:2307.11088**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/) 4. [**ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing arXiv:2306.00622**Ryan Liu, Nihar B. Shah*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-reviewergpt-exploratory-study-using/) 5. **[Is LLM a Reliable Reviewer? A Comprehensive Evaluation of LLM on Automatic Paper Reviewing Tasks](https://md.research.elamur.ai/free/en/papers/zhou-2024-is-llm-reliable-reviewer-comprehensive/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ruiyang Zhou, Lu Chen, Kai Yu*2024 · 74 citations* 6. **[LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://md.research.elamur.ai/free/en/papers/du-2024-llms-assist-nlp-researchers-critique/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiangshu Du, Yibo Wang, Wenting Zhao, et al.*2024 · 71 citations* 7. **[NLPeer: A Unified Resource for the Computational Study of Peer Review](https://md.research.elamur.ai/free/en/papers/dycke-2023-nlpeer-unified-resource-computational-study/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nils Dycke, Ilia Kuznetsov, Iryna Gurevych*2023 · 64 citations* 8. **[Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review](https://md.research.elamur.ai/free/en/papers/kuznetsov-2022-revise-resubmit-intertextual-model-text/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ilia Kuznetsov, Jan Buchmann, Max Eichler, et al.*2022 · 54 citations* 9. [**Reviewer2: Optimizing Review Generation Through Prompt Generation arXiv:2402.10886**Zhaolin Gao, Kiante Brantley, Thorsten Joachims*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-reviewer2-optimizing-review-generation-through/) 10. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations* 11. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations* 12. **[TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review](https://md.research.elamur.ai/free/en/papers/chang-2025-treereview-dynamic-tree-questions-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuan Chang, Ziyue Li, Hengyuan Zhang, et al.*2025 · 16 citations* 13. **[Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM Reviews](https://md.research.elamur.ai/free/en/papers/shin-2025-mind-blind-spots-focus-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, et al.*2025 · 14 citations* 14. **[Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework](https://md.research.elamur.ai/free/en/papers/dycke-2026-automatic-reviewers-fail-detect-faulty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nils Dycke, Iryna Gurevych*2026 · 5 citations* 15. **[NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment](https://md.research.elamur.ai/free/en/papers/wu-2026-novbench-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqing Wu, Yi Zhao, Yuzhuo Wang, et al.*2026 · 4 citations* 16. **[RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation](https://md.research.elamur.ai/free/en/papers/wu-2026-rbtact-rebuttal-as-supervision-actionable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihong Wu, Yiling Ma, Yilun Zhao, et al.*2026 · 2 citations* 17. **[NUS-IDS at PragTag-2023: Improving Pragmatic Tagging of Peer Reviews through Unlabeled Data](https://md.research.elamur.ai/free/en/papers/gollapalli-2023-nus-ids-pragtag-2023-improving/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Sujatha Das Gollapalli, Yixin Huang, See-Kiong Ng*2023 · 2 citations* 18. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation* 19. **[PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers in Overleaf](https://md.research.elamur.ai/free/en/papers/liu-2026-papermentor-human-centered-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner, et al.*2026 · 1 citation* 20. **[Implicit Bias in Peer Review: Through the Lens of Language Abstraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-implicit-bias-peer-review-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Xulang Zhang, Rui Mao, Erik Cambria*2026* 49 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/) — Can We Automate Scientific Reviewing?