--- title: "Who cites Mengyu Zhou — 90 papers of our library" description: "90 papers of the Elamur Research library cite the works of Mengyu Zhou, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/mengyu-zhou/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/mengyu-zhou/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Mengyu Zhou](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/) / cited by # Who cites Mengyu Zhou 92 citations of their works from 90 papers of our library (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← Mengyu Zhou](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/) 1. **[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* 2. **[AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research](https://md.research.elamur.ai/free/en/papers/zhao-2025-abgen-evaluating-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Weiyuan Chen, Zhijian Xu, et al.*2025 · 9 citations* 3. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations* 4. **[TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-tableeval-real-world-benchmark-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Jingyi Wang, Bohan Yu, et al.*2025 · 7 citations* 5. **[When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables](https://md.research.elamur.ai/free/en/papers/ye-2026-when-tableqa-meets-noise-dual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenghao Ye, Yu Guo, Dong Jin, et al.*2026 · 4 citations* 6. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations* 7. [**AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data arXiv:2507.18442**Rana Alshaikh, Israa Alghanmi, Shelan Jeawak*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alshaikh-2025-aratable-benchmarking-llms-reasoning-understanding/) 8. **[CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning](https://md.research.elamur.ai/free/en/papers/nguyen-2026-coretab-improving-multimodal-table-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van-Quang Nguyen, Takayuki Okatani*2026 · 1 citation* 9. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation* 10. **[The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs](https://md.research.elamur.ai/free/en/papers/tahan-2026-mighty-torr-benchmark-table-reasoning/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Shir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.*2026 · 1 citation* 11. **[Applicability Condition Extraction for Therapeutic Drug-Disease Relations](https://md.research.elamur.ai/free/en/papers/luo-2026-applicability-condition-extraction-therapeutic-drug/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guanting Luo, Noriki Nishida, Yuji Matsumoto, et al.*2026* 12. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026* 13. **[Can LLMs Self-Correct Table Reasoning Errors?](https://md.research.elamur.ai/free/en/papers/shaikh-2026-can-llms-self-correct-table/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Farseen Shaikh*2026* 14. **[From Rules to Predictions: Federated Tabular Learning with LLM Reasoning](https://md.research.elamur.ai/free/en/papers/mahanipour-2026-rules-predictions-federated-tabular-learning/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Afsaneh Mahanipour, Hana Khamfroush*2026* 15. **[LLM-FK: Multi-Agent LLM Reasoning for Foreign Key Detection in Large-Scale Complex Databases](https://md.research.elamur.ai/free/en/papers/tang-2026-llm-fk-multi-agent-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Tang, Ying Zhang, Sibo Cai, et al.*2026* 16. **[Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses](https://md.research.elamur.ai/free/en/papers/nguyen-2026-questionnaire-meets-llm-benchmark-empirical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, et al.*2026* 17. **[Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning](https://md.research.elamur.ai/free/en/papers/ren-2026-robust-real-world-spreadsheet-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houxing Ren, Mingjie Zhan, Zimu Lu, et al.*2026* 73 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/) — Mengyu Zhou