--- title: "Who cites Multimodal Table Understanding — 36 citing papers" description: "36 papers of the Elamur Research library cite «Multimodal Table Understanding», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Multimodal Table Understanding](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) / cited by # Who cites «Multimodal Table Understanding» 36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Multimodal Table Understanding»](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) 1. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/) 2. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/) 3. **[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* 4. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/) 5. **[SciVer: Evaluating Foundation Models for Multimodal Scientific Claim Verification](https://md.research.elamur.ai/free/en/papers/wang-2025-sciver-evaluating-foundation-models-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengye Wang, Yifei Shen, Zexi Kuang, et al.*2025 · 11 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. **[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* 8. **[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* 9. **[Learning Flexible Large Multimodal Models with Arbitrary Modality Combinations](https://md.research.elamur.ai/free/en/papers/zhao-2026-learning-flexible-large-multimodal-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhao, Kangqi Ni, Jie Peng, et al.*2026* 10. **[MMTabReal: Real-World Benchmark for Multimodal Table Understanding](https://md.research.elamur.ai/free/en/papers/titiya-2026-mmtabreal-real-world-benchmark-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Prasham Yatinkumar Titiya, Jainil Trivedi, Chitta Baral, et al.*2026* 11. **[TableVista: Benchmarking Multimodal Table Reasoning under Visual and Structural Complexity](https://md.research.elamur.ai/free/en/papers/yang-2026-tablevista-benchmarking-multimodal-table-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Yang, Liqiang Shang, Junjie Chen, et al.*2026* 12. **[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* 24 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) — Multimodal Table Understanding