---
title: "Who cites Yilun Zhou — 117 papers of our library"
description: "117 papers of the Elamur Research library cite the works of Yilun Zhou, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yilun-zhou/cited-by/"
---
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# Who cites Yilun Zhou

123 citations of their works from 117 papers of our library (of the 149,439 whose bibliographies we read) · 42 with a page here, the most cited first · [← Yilun Zhou](https://md.research.elamur.ai/free/en/authors/yilun-zhou/)

1. [**Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers arXiv:2409.04109**Chenglei Si, Diyi Yang, Tatsunori Hashimoto*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/si-2024-llms-generate-novel-research/)
2. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
3. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
4. [**Agent Laboratory: Using LLM Agents as Research Assistants arXiv:2501.04227**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 139 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
5. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
6. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs arXiv:2410.18451**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
7. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
8. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
9. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
10. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations*
11. **[Lost in Multilinguality: Dissecting Cross-lingual Factual Inconsistency in Transformer Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-lost-multilinguality-dissecting-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyang Wang, Heike Adel, Lukas Lange, et al.*2025 · 31 citations*
12. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
13. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
14. **[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*
15. **[Improve LLM-as-a-Judge Ability as a General Ability](https://md.research.elamur.ai/free/en/papers/yu-2025-improve-llm-as-judge-ability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiachen Yu, Shaoning Sun, Xiaohui Hu, et al.*2025 · 15 citations*
16. **[Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings](https://md.research.elamur.ai/free/en/papers/xu-2025-does-context-matter-contextualjudgebench-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Srijan Bansal, Yifei Ming, et al.*2025 · 14 citations*
17. **[FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging](https://md.research.elamur.ai/free/en/papers/tang-2025-financereasoning-benchmarking-financial-numerical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zichen Tang, Haihong E, Ziyan Ma, et al.*2025 · 13 citations*
18. [**U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs arXiv:2412.03205**Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chernyshev-2024-u-math-university-level-benchmark/)
19. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
20. **[The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis](https://md.research.elamur.ai/free/en/papers/mueller-2026-quest-right-mediator-surveying-mechanistic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aaron Mueller, Jannik Brinkmann, Millicent Li, et al.*2026 · 7 citations*
21. **[Internal Chain-of-Thought: Empirical Evidence for Layer-wise Subtask Scheduling in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-internal-chain-thought-empirical-evidence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhipeng Yang, Junzhuo Li, Siyu Xia, et al.*2025 · 7 citations*
22. [**Shared Imagination: LLMs Hallucinate Alike arXiv:2407.16604**Yilun Zhou, Caiming Xiong, Silvio Savarese, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-shared-imagination-llms-hallucinate-alike/)
23. **[All for One: LLMs Solve Mental Math at the Last Token With Information Transferred From Other Tokens](https://md.research.elamur.ai/free/en/papers/mamidanna-2025-all-one-llms-solve-mental/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siddarth Mamidanna, Daking Rai, Ziyu Yao, et al.*2025 · 6 citations*
24. [**Give me a hint: Can LLMs take a hint to solve math problems? arXiv:2410.05915**Vansh Agrawal, Pratham Singla, Amitoj Singh Miglani, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-give-me-hint-llms-take/)
25. **[DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-dars-dynamic-action-re-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.*2025 · 4 citations*
26. **[EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving](https://md.research.elamur.ai/free/en/papers/zhou-2026-engibench-benchmark-evaluating-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiyuan Zhou, Xinlei Wang, Yirui He, et al.*2026 · 3 citations*
27. **[J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-j4r-learning-judge-equivalent-initial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.*2026 · 3 citations*
28. **[IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-critic-fine-grained-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
29. **[SSA: Improving Performance With a Better Scoring Function](https://md.research.elamur.ai/free/en/papers/naim-2026-ssa-improving-performance-better-scoring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Omar Naim, Swarnadeep Bhar, Jerome Bolte, et al.*2026 · 1 citation*
30. **[Tug-of-war between idioms' figurative and literal interpretations in LLMs](https://md.research.elamur.ai/free/en/papers/oh-2026-tug-war-between-idioms-figurative/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Soyoung Oh, Xinting Huang, Mathis Pink, et al.*2026 · 1 citation*
31. **[A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-survey-multimodal-mathematical-reasoning-perception/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Sihong Wu, Yilun Zhao, et al.*2026*
32. **[AdaptiveK: Complexity-Driven Sparse Autoencoders for Interpretable Language Model Representations](https://md.research.elamur.ai/free/en/papers/yao-2026-adaptivek-complexity-driven-sparse-autoencoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifei Yao, Hanrong Zhang, Mengnan Du*2026*
33. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
34. **[Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*
35. **[FIBER: A Multilingual Evaluation Resource for Factual Inference Bias](https://md.research.elamur.ai/free/en/papers/munis-2026-fiber-multilingual-evaluation-resource-factual/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Evren Ayberk Munis, Deniz Yilmaz, Arianna Muti, et al.*2026*
36. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
37. **[GeoLAN: Geometric Learning of Latent Explanatory Directions in Large Language Models](https://md.research.elamur.ai/free/en/papers/pan-2026-geolan-geometric-learning-latent-explanatory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Pan, Damon L. Woodard*2026*
38. **[Mechanistic Interpretability Meets Cognitive Linguistics: Modelling Locative Image Schemas in the Circuit Framework](https://md.research.elamur.ai/free/en/papers/proietti-2026-mechanistic-interpretability-meets-cognitive-linguistics/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mattia Proietti, Afra Alishahi, Grzegorz Chrupała, et al.*2026*
39. **[Revitalizing Black-Box Interpretability: Actionable Interpretability for LLMs via Proxy Models](https://md.research.elamur.ai/free/en/papers/liu-2026-revitalizing-black-box-interpretability-actionable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junhao Liu, Haonan Yu, Zhenyu Yan, et al.*2026*
40. **[Temporal Token Matters: Investigating and Interpreting the Consistency of Temporal Ordering in Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-temporal-token-matters-investigating-interpreting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Yang, Xinyue Zhang, Ping Jian, et al.*2026*
41. **[The Shape of Vulnerability: How Adversarial Perturbations Reshape the Topology of Language Model Latent Spaces](https://md.research.elamur.ai/free/en/papers/tsai-2026-shape-vulnerability-how-adversarial-perturbations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Angelina Tsai, Shreya Subramanian, Catherine Liu, et al.*2026*
42. **[Word Surprisal Correlates with Sentential Contradiction in LLMs](https://md.research.elamur.ai/free/en/papers/shi-2026-word-surprisal-correlates-sentential-contradiction/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ning Shi, Bradley Hauer, David Basil, et al.*2026*

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