---
title: "Who cites CharXiv: Charting Gaps in — 94 citing papers"
description: "94 papers of the Elamur Research library cite «CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs», found in their…"
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---
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# Who cites «CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs»

94 papers of our library cite it (of the 149,439 whose bibliographies we read) · 39 with a page here, the most cited first · [← back to «CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs»](https://md.research.elamur.ai/free/en/papers/wang-2024-charxiv-charting-gaps-realistic-chart/)

1. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
2. [**Qwen3-VL Technical Report arXiv:2511.21631**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 370 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
3. [**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/)
4. [**OpenAI GPT-5 System Card arXiv:2601.03267**Aaditya Singh, Adam Fry, Adam Perelman, et al.*2025 · 279 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-openai-gpt-5-system-card/)
5. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
6. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
7. **[A Thorough Examination of Decoding Methods in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/shi-2024-thorough-examination-decoding-methods-era/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chufan Shi, Haoran Yang, Deng Cai, et al.*2024 · 68 citations*
8. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
9. [**Kimi K2.5: Visual Agentic Intelligence arXiv:2602.02276**Kimi Team, Tongtong Bai, Yifan Bai, et al.*2026 · 66 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2026-kimi-k2-5-visual/)
10. [**MiMo-VL Technical Report arXiv:2506.03569**Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-vl-technical-report/)
11. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
12. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
13. **[ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation](https://md.research.elamur.ai/free/en/papers/zhao-2025-chartcoder-advancing-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanle Zhao, Xianzhen Luo, Qi Shi, et al.*2025 · 24 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. [**MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding arXiv:2407.04903**Zekun Li, Xianjun Yang, Kyuri Choi, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-mmsci-dataset-graduate-level-multi/)
16. **[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*
17. [**ERNIE 5.0 Technical Report arXiv:2602.04705**Haifeng Wang, Hua Wu, Tian Wu, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-ernie-5-0-technical/)
18. **[ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/loison-2026-vidore-v3-comprehensive-evaluation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**António Loison, Quentin Macé, Antoine Edy, et al.*2026 · 7 citations*
19. **[ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering](https://md.research.elamur.ai/free/en/papers/kaur-2026-chartagent-multimodal-agent-visually-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rachneet Kaur, Nishan Srishankar, Zhen Zeng, et al.*2026 · 5 citations*
20. **[ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch](https://md.research.elamur.ai/free/en/papers/liu-2026-chartverse-scaling-chart-reasoning-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Liu, Honglin Lin, Xiaoyang Wang, et al.*2026 · 5 citations*
21. **[FinChart-Bench: Benchmarking Financial Chart Comprehension in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/shu-2026-finchart-bench-benchmarking-financial-chart/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dong Shu, Haoyang Yuan, Yuchen Wang, et al.*2026 · 3 citations*
22. **[From Charts to Code: A Hierarchical Benchmark for Multimodal Models](https://md.research.elamur.ai/free/en/papers/tang-2026-charts-code-hierarchical-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu, et al.*2026 · 3 citations*
23. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
24. **[POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering](https://md.research.elamur.ai/free/en/papers/xu-2026-polychartqa-benchmarking-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichen Xu, Liangyu Chen, Liang Zhang, et al.*2026 · 2 citations*
25. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
26. **[ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2026-arise-adaptive-resolution-aware-metric/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyue Yin, Qiushi Sun, Zhiyuan Zeng, et al.*2026 · 1 citation*
27. **[Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chart-rl-generalized-chart-comprehension/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Xin Zhang, Xingyu Li, Rongguang Wang, et al.*2026 · 1 citation*
28. **[Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images](https://md.research.elamur.ai/free/en/papers/zhang-2026-structured-abstractive-reasoning-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichi Zhang, Zhuo Chen, Lingbing Guo, et al.*2026 · 1 citation*
29. **[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*
30. **[Automatic and Reliable Evaluation for Academic Caption-to-Figure Generation with LMMs](https://md.research.elamur.ai/free/en/papers/ye-2026-automatic-reliable-evaluation-academic-caption/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanghui Ye, Huan Zhao, Qin Zhu, et al.*2026*
31. **[ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts](https://md.research.elamur.ai/free/en/papers/ye-2026-chartdiff-large-scale-benchmark-comprehending/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Rongtian Ye*2026*
32. **[Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards](https://md.research.elamur.ai/free/en/papers/niu-2026-dashboard2code-evaluating-multimodal-models-reconstructing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhao Niu, Ziyu Han, Qiguang Chen, et al.*2026*
33. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026*
34. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026*
35. **[PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers](https://md.research.elamur.ai/free/en/papers/xiong-2026-paperscope-multi-modal-multi-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Xiong, Huaying Yuan, Zheng Liu, et al.*2026*
36. **[PlotGen-Bench: Evaluating VLMs on Generating Visualization Code from Diverse Plots across Multiple Libraries](https://md.research.elamur.ai/free/en/papers/zhao-2026-plotgen-bench-evaluating-vlms-generating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Zhao, Zhen Yang, Shuaiqi Duan, et al.*2026*
37. [**Qwen3.8-Omni: Towards Native Omni-Modal Agents arXiv:2609.25611**Qwen Team*2026*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-8-omni-native/)
38. **[Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool Composition](https://md.research.elamur.ai/free/en/papers/wang-2026-simple-vgc-enhancing-visual-grounding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye Wang, Qianglong Chen, Siyuan Wang, et al.*2026*
39. **[SimpleOCR: Rendering Visual Questions to Teach MLLMs to Read](https://md.research.elamur.ai/free/en/papers/peng-2026-simpleocr-rendering-visual-questions-teach/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Peng, Peng Xia, Ding Zhong, et al.*2026*

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

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