🔗 Who cites «IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning»

94 papers of our library cite it (of the 149,439 whose bibliographies we read) · 45 with a page here, the most cited first · ← back to «IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning»

1. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
2. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
3. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
4. InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic TasksarXiv:2312.14238Zhe Chen, Jiannan Wu, Wenhai Wang, et al.2023 · 435 citations
5. Chameleon: Plug-and-Play Compositional Reasoning with Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Pan Lu, Baolin Peng, Hao Cheng, et al.2023 · 327 citations
6. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
7. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
8. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
9. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
10. Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical ReasoningarXiv:2209.14610Pan Lu, Liang Qiu, Kai-Wei Chang, et al.2022 · 219 citations
11. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
12. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
13. Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
14. DeepSeek-VL: Towards Real-World Vision-Language UnderstandingarXiv:2403.05525Haoyu Lu, Wen Liu, Bo Zhang, et al.2024 · 208 citations
15. MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
16. LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 179 citations
17. TheoremQA: A Theorem-driven Question Answering DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Ming Yin, Max Ku, et al.2023 · 158 citations
18. SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language ModelsarXiv:2307.10635Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.2023 · 149 citations
19. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 137 citations
20. LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 115 citations
21. Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.2024 · 112 citations
22. UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical ExpressionConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaqi Chen, Tong Li, Jinghui Qin, et al.2022 · 111 citations
23. Large language models for education: A survey and outlookWang2024 · 101 citations
24. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
25. InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and CompositionarXiv:2309.15112Pan Zhang, Xiaoyi Dong, Bin Wang, et al.2023 · 87 citations
26. Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language ModelsFindings of the Association for Computational LinguisticsWenhao Shi, Zhiqiang Hu, Yi Bin, et al.2024 · 86 citations
27. mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language ModelsarXiv:2408.04840Jiabo Ye, Haiyang Xu, Haowei Liu, et al.2024 · 60 citations
28. MMICL: Empowering Vision-language Model with Multi-Modal In-Context LearningarXiv:2309.07915Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.2023 · 58 citations
29. Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language ModelsarXiv:2305.16582Yao Yao, Zuchao Li, Hai Zhao2023 · 55 citations
30. InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDConference on Neural Information Processing Systems (NeurIPS)Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 54 citations
31. CogVLM2: Visual Language Models for Image and Video UnderstandingarXiv:2408.16500Wenyi Hong, Weihan Wang, Ming Ding, et al.2024 · 52 citations
32. JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionYiyang Ma, Xingchao Liu, Xiaokang Chen, et al.2024 · 52 citations
33. NVLM: Open Frontier-Class Multimodal LLMsarXiv:2409.11402Wenliang Dai, Nayeon Lee, Boxin Wang, et al.2024 · 44 citations
34. MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at ScaleAnnual Meeting of the Association for Computational Linguistics (ACL)Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.2025 · 40 citations
35. InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and OutputarXiv:2407.03320Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.2024 · 39 citations
36. Baichuan-Omni-1.5 Technical ReportarXiv:2501.15368Yadong Li, Jun Liu, Tao Zhang, et al.2025 · 28 citations
37. LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Jinhe Bi, Yujun Wang, Haokun Chen, et al.2025 · 24 citations
38. CAMEL-Bench: A Comprehensive Arabic LMM BenchmarkFindings of the Association for Computational LinguisticsSara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.2025 · 22 citations
39. GAOKAO-MM: A Chinese Human-Level Benchmark for Multimodal Models EvaluationarXiv:2402.15745Yi Zong, Xipeng Qiu2024 · 11 citations
40. Centurio: On Drivers of Multilingual Ability of Large Vision-Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.2025 · 9 citations
41. CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question AnsweringFindings of the Association for Computational LinguisticsXiyin Zeng, Yi Lu, Hao Wang2026 · 1 citation
42. GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs?arXiv:2412.10056Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.2024 · 1 citation
43. A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Yang, Sihong Wu, Yilun Zhao, et al.2026
44. Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task EvaluationFindings of the Association for Computational LinguisticsQiong Wu, Tan Yue, Jianxin Liang, et al.2026
45. Targeted Exploration via Unified Entropy Control for Reinforcement LearningFindings of the Association for Computational LinguisticsChen Wang, Lai Wei, Yanzhi Zhang, et al.2026

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