🔗 Who cites «Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study»

87 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← back to «Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study»

1. Retrieval-Augmented Generation with Graphs (GraphRAG)arXiv:2501.00309Haoyu Han, Yu Wang, Harry Shomer, et al.2025 · 87 citations
2. GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and BenchmarkingarXiv:2305.15066Jiayan Guo, Lun Du, Hengyu Liu, et al.2023 · 75 citations
3. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
4. AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific ResearchAnnual Meeting of the Association for Computational Linguistics (ACL)Yilun Zhao, Weiyuan Chen, Zhijian Xu, et al.2025 · 9 citations
5. TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyi He, Yihao Liu, Mengyu Zhou, et al.2025 · 8 citations
6. TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Junnan Zhu, Jingyi Wang, Bohan Yu, et al.2025 · 7 citations
7. When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale TablesAnnual Meeting of the Association for Computational Linguistics (ACL)Shenghao Ye, Yu Guo, Dong Jin, et al.2026 · 4 citations
8. AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular DataarXiv:2507.18442Rana Alshaikh, Israa Alghanmi, Shelan Jeawak2025 · 2 citations
9. CoReTab: Improving Multimodal Table Understanding with Code-driven ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Van-Quang Nguyen, Takayuki Okatani2026 · 1 citation
10. Efficient Table Retrieval and Understanding with Multimodal Large Language ModelsFindings of the Association for Computational LinguisticsZhuoyan Xu, Haoyang Fang, Boran Han, et al.2026 · 1 citation
11. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMsWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraShir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.2026 · 1 citation
12. AFT-Tab: Adversarial Fine-Tuning for Tabular Data Synthesis with Long Text ColumnsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhao Zhang, Liang Yan, Shaoming Duan, et al.2026
13. Asking language models how to represent data for fine-tuningWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraUsneek Singh, Ananya Singha, Abhijeet Awasthi, et al.2026
14. Can LLMs Self-Correct Table Reasoning Errors?Workshop on Structured Understanding, Retrieval, and Generation in the LLM EraFarseen Shaikh2026
15. EvoSci: A Bio-Inspired Multi-Agent Framework for the Evolution of Scientific DiscoveryAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Xiong, Yuqi Ren, Deyi Xiong2026
16. From Rules to Predictions: Federated Tabular Learning with LLM ReasoningBioNLPAfsaneh Mahanipour, Hana Khamfroush2026
17. Generalizable LLM Learning of Graph Synthetic Data with Post-training AlignmentFindings of the Association for Computational LinguisticsYizhuo Zhang, Heng Wang, Shangbin Feng, et al.2026
18. LLM-FK: Multi-Agent LLM Reasoning for Foreign Key Detection in Large-Scale Complex DatabasesFindings of the Association for Computational LinguisticsZijian Tang, Ying Zhang, Sibo Cai, et al.2026
19. Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhang Zhou, Mingrui Zhang, Ke Li, et al.2026
20. Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and ResponsesLanguage Resources and Evaluation Conference (LREC)Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, et al.2026
21. Table-R1: Region-based Reinforcement Learning for Table UnderstandingFindings of the Association for Computational LinguisticsZhenhe Wu, Jian Yang, Zhongjiang He, et al.2026
22. Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Houxing Ren, Mingjie Zhan, Zimu Lu, et al.2026

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

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