🔗 Who cites «AI-Driven Review Systems: Evaluating LLMs in Scalable and Bias-Aware Academic Reviews»

26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · ← back to «AI-Driven Review Systems: Evaluating LLMs in Scalable and Bias-Aware Academic Reviews»

1. CycleResearcher: Improving Automated Research via Automated ReviewarXiv:2411.00816Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.2024 · 65 citations
2. DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking ProcessAnnual Meeting of the Association for Computational Linguistics (ACL)Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2025 · 52 citations
3. From Automation to Autonomy: A Survey on Large Language Models in Scientific DiscoveryConference on Empirical Methods in Natural Language Processing (EMNLP)Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.2025 · 39 citations
4. Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer ReviewarXiv:2412.01708Rui Ye, Xianghe Pang, Jingyi Chai, et al.2024 · 35 citations
5. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
6. Curie: Toward Rigorous and Automated Scientific Experimentation with AI AgentsarXiv:2502.16069Patrick Tser Jern Kon, Jiachen Liu, Qiuyi Ding, et al.2025 · 20 citations
7. Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM ReviewsConference on Empirical Methods in Natural Language Processing (EMNLP)Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, et al.2025 · 14 citations
8. Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer RewardsarXiv:2505.04966Jaeho Kim, Yunseok Lee, Seulki Lee2025 · 13 citations
9. Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research PapersAnnual Meeting of the Association for Computational Linguistics (ACL)Zhijian Xu, Yilun Zhao, Manasi Patwardhan, et al.2025 · 11 citations
10. Evaluating Sakana's AI Scientist: Bold Claims, Mixed Results, and a Promising Future?arXiv:2502.14297 · SIGIR Forum 2025Joeran Beel, Min-Yen Kan, Moritz Baumgart2025 · 11 citations
11. Reviewing Scientific Papers for Critical Problems With Reasoning LLMs: Baseline Approaches and Automatic EvaluationarXiv:2505.23824Tianmai M. Zhang, Neil F. Abernethy2025 · 7 citations
12. Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation FrameworkTransactions of the Association for Computational Linguistics (TACL)Nils Dycke, Iryna Gurevych2026 · 5 citations
13. Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the FutureAnnual Meeting of the Association for Computational Linguistics (ACL)Sihong Wu, Owen Jiang, Yilun Zhao, et al.2026 · 1 citation
14. From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper EvaluationFindings of the Association for Computational LinguisticsPujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.2026

12 more papers of our library cite it; they have no page here yet.

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