--- title: "Who cites Are We There Yet? Revealing the — 26 citing papers" description: "26 papers of the Elamur Research library cite «Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer…" canonical: "https://research.elamur.ai/free/en/papers/ye-2024-there-yet-revealing-risks/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ye-2024-there-yet-revealing-risks/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Are We There Yet? Revealing the Risks of…](https://md.research.elamur.ai/free/en/papers/ye-2024-there-yet-revealing-risks/) / cited by # Who cites «Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review» 26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review»](https://md.research.elamur.ai/free/en/papers/ye-2024-there-yet-revealing-risks/) 1. **[DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Process](https://md.research.elamur.ai/free/en/papers/zhu-2025-deepreview-improving-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minjun Zhu, Yixuan Weng, Linyi Yang, et al.*2025 · 52 citations* 2. **[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* 3. **[MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research](https://md.research.elamur.ai/free/en/papers/chen-2025-mlr-bench-evaluating-ai/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hui Chen, Miao Xiong, Yujie Lu, et al.*2025 · 21 citations* 4. **[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* 5. [**Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards arXiv:2505.04966**Jaeho Kim, Yunseok Lee, Seulki Lee*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-position-ai-conference-peer-review/) 6. [**Evaluating Sakana's AI Scientist: Bold Claims, Mixed Results, and a Promising Future? arXiv:2502.14297 · SIGIR Forum 2025**Joeran Beel, Min-Yen Kan, Moritz Baumgart*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/beel-2025-evaluating-sakana-s-ai/) 7. **[Justice in Judgment: Unveiling (Hidden) Bias in LLM-assisted Peer Reviews](https://md.research.elamur.ai/free/en/papers/vasu-2026-justice-judgment-unveiling-hidden-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sai Suresh Macharla Vasu, Ivaxi Sheth, Hui-Po Wang, et al.*2026 · 8 citations* 8. **[Hidden Prompts in Manuscripts Exploit AI-Assisted Peer Review](https://md.research.elamur.ai/free/en/papers/lin-2025-hidden-prompts-manuscripts-exploit/) [Communications of the ACM](https://md.research.elamur.ai/free/en/venues/communications-of-the-acm/)**Zhicheng Lin*2025 · 7 citations* 9. [**Reviewing Scientific Papers for Critical Problems With Reasoning LLMs: Baseline Approaches and Automatic Evaluation arXiv:2505.23824**Tianmai M. Zhang, Neil F. Abernethy*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-reviewing-scientific-papers-critical-problems/) 10. [**AI for Auto-Research: Roadmap & User Guide arXiv:2605.18661**Lingdong Kong, Xian Sun, Wei Chow, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kong-2026-ai-auto-research-roadmap-user/) 11. [**"Give a Positive Review Only": An Early Investigation Into In-Paper Prompt Injection Attacks and Defenses for AI Reviewers arXiv:2511.01287**Qin Zhou, Zhexin Zhang, Zhi Li, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-give-positive-review-only/) 12. **[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* 13. **[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* 13 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ye-2024-there-yet-revealing-risks/) — Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review