---
title: "Who cites Haokun Lin — 170 papers of our library"
description: "170 papers of the Elamur Research library cite the works of Haokun Lin, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/haokun-lin/cited-by/"
---
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# Who cites Haokun Lin

170 citations of their works from 170 papers of our library (of the 149,439 whose bibliographies we read) · 70 with a page here, the most cited first · [← Haokun Lin](https://md.research.elamur.ai/free/en/authors/haokun-lin/)

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. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
3. **[Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 427 citations*
4. [**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/)
5. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention arXiv:2303.16199**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
6. [**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/)
7. [**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/)
8. [**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/)
9. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
10. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
11. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
12. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
13. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
14. [**Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models arXiv:2503.06749**Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-vision-r1-incentivizing-reasoning-capability/)
15. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
16. **[Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2024-math-llava-bootstrapping-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Shi, Zhiqiang Hu, Yi Bin, et al.*2024 · 86 citations*
17. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
18. [**MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark arXiv:2410.19168**S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/sakshi-2024-mmau-massive-multi-task-audio/)
19. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
20. **[OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Huang, Zengzhi Wang, Shijie Xia, et al.*2024 · 56 citations*
21. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
22. [**SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models arXiv:2504.11468**Hardy Chen, Haoqin Tu, Fali Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-sft-rl-early-investigation-training/)
23. **[Vision-Language Models Can Self-Improve Reasoning via Reflection](https://md.research.elamur.ai/free/en/papers/cheng-2025-vision-language-models-can-self/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.*2025 · 35 citations*
24. [**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/)
25. [**MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe arXiv:2509.18154**Tianyu Yu, Zefan Wang, Chongyi Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-minicpm-v-4-5/)
26. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
27. **[MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification](https://md.research.elamur.ai/free/en/papers/sun-2025-mm-verify-enhancing-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.*2025 · 19 citations*
28. [**CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning arXiv:2503.13517**Hao Cui, Zahra Shamsi, Gowoon Cheon, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-curie-evaluating-llms-multitask-scientific/)
29. [**U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs arXiv:2412.03205**Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chernyshev-2024-u-math-university-level-benchmark/)
30. **[Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2025-mitigating-visual-forgetting-take-along/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hai-Long Sun, Zhun Sun, Houwen Peng, et al.*2025 · 12 citations*
31. **[Progressive Multimodal Reasoning via Active Retrieval](https://md.research.elamur.ai/free/en/papers/dong-2025-progressive-multimodal-reasoning-active-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.*2025 · 10 citations*
32. [**MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model arXiv:2409.13729**Zhen Yang, Jinhao Chen, Zhengxiao Du, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-mathglm-vision-solving-mathematical-problems/)
33. **[ViLBench: A Suite for Vision-Language Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/tu-2025-vilbench-suite-vision-language-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoqin Tu, Weitao Feng, Hardy Chen, et al.*2025 · 9 citations*
34. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
35. **[Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems](https://md.research.elamur.ai/free/en/papers/ye-2024-assessing-creativity-llms-proposing-novel/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Junyi Ye, Jingyi Gu, Xinyun Zhao, et al.*2024 · 8 citations*
36. [**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/)
37. [**Skywork-R1V3 Technical Report arXiv:2507.06167**Wei Shen, Jiangbo Pei, Yi Peng, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/)
38. **[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*
39. **[Unlocking Multilingual Reasoning Capability of LLMs and LVLMs through Representation Engineering](https://md.research.elamur.ai/free/en/papers/li-2026-unlocking-multilingual-reasoning-capability-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiming Li, Xiaocheng Feng, Yixuan Ma, et al.*2026 · 4 citations*
40. **[MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2026-mathcanvas-intrinsic-visual-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weikang Shi, Aldrich Yu, Rongyao Fang, et al.*2026 · 3 citations*
41. **[SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis](https://md.research.elamur.ai/free/en/papers/wu-2026-synthrl-scaling-visual-reasoning-verifiable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Wu, Jinjie Ni, Xiangyan Liu, et al.*2026 · 3 citations*
42. **[GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-gm-prm-generative-multimodal-process/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Jianghangfan Zhang, Yibo Yan, Kening Zheng, et al.*2026 · 2 citations*
43. **[IREASONER: Trajectory-Aware Intrinsic Reasoning Supervision for Self-Evolving Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/sunil-2026-ireasoner-trajectory-aware-intrinsic-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meghana Sunil, Manikandarajan Venmathimaran, Muthu Subash Kavitha*2026 · 2 citations*
44. [**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/)
45. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation*
46. **[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*
47. **[Compatibility-Aware Dynamic Fine-Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-compatibility-aware-dynamic-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Junwei Sheng, Qianning Wang, et al.*2026 · 1 citation*
48. **[MMErroR: A Benchmark for Erroneous Reasoning in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-mmerror-benchmark-erroneous-reasoning-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Shi, Yifeng Xie, Minzhe Guo, et al.*2026 · 1 citation*
49. **[RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction](https://md.research.elamur.ai/free/en/papers/park-2026-ra-rrg-multimodal-retrieval-augmented/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jonggwon Park, Byungmu Yoon, Soobum Kim, et al.*2026 · 1 citation*
50. **[Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/xu-2026-seeing-but-not-thinking-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haolei Xu, Haiwen Hong, Hongxing Li, et al.*2026 · 1 citation*
51. **[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*
52. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/)
53. **[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*
54. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
55. **[Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task Evaluation](https://md.research.elamur.ai/free/en/papers/wu-2026-curriculum-learning-based-hierarchical-scoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiong Wu, Tan Yue, Jianxin Liang, et al.*2026*
56. **[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*
57. **[Do Multi-Agents Solve Better Than Single? Evaluating Agentic Frameworks for Diagram-Grounded Geometry Problem Solving and Reasoning](https://md.research.elamur.ai/free/en/papers/sobhani-2026-do-multi-agents-solve-better/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mahbub E Sobhani, Md. Faiyaz Abdullah Sayeedi, Mohammad Nehad Alam, et al.*2026*
58. **[EduMARS: Can Vision-Language Models Grade Like Teachers? Benchmarking Multimodal, Rubric-Based Assessment on Chinese K-12 Answers](https://md.research.elamur.ai/free/en/papers/zhao-2026-edumars-can-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Zhao, Jiashun Chen, Wanting xu, et al.*2026*
59. **[Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal Language](https://md.research.elamur.ai/free/en/papers/wang-2026-geoparsing-diagram-parsing-plane-solid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peijie Wang, Ming-Liang Zhang, Jun Cao, et al.*2026*
60. **[Investigating Cross-Modal Skill Injection: Scenarios, Methods, and Hyperparameters](https://md.research.elamur.ai/free/en/papers/xu-2026-investigating-cross-modal-skill-injection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Xu, Lean Wang, Yuanxin Liu, et al.*2026*
61. **[MathSight: A Benchmark Exploring Have Vision-Language Models Really Seen in University-Level Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/wang-2026-mathsight-benchmark-exploring-have-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuandong Wang, Yao Cui, Yuxin Zhao, et al.*2026*
62. **[Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/sinha-2026-mind-s-eye-benchmark-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.*2026*
63. **[Minimal Free Resolution Guided Adaptive Tree Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-minimal-free-resolution-guided-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dezhao Tang, Meihan Liu, Yulai Tong, et al.*2026*
64. **[MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring](https://md.research.elamur.ai/free/en/papers/yang-2026-mmtutorbench-first-multimodal-benchmark-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tengchao Yang, Sichen Guo, Mengzhao Jia, et al.*2026*
65. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
66. **[PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models](https://md.research.elamur.ai/free/en/papers/ouyang-2026-pyramathbench-evaluating-improving-mathematical-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zetian Ouyang, Linlin Wang, Gerard de Melo, et al.*2026*
67. **[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*
68. **[Targeted Exploration via Unified Entropy Control for Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-targeted-exploration-unified-entropy-control/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Wang, Lai Wei, Yanzhi Zhang, et al.*2026*
69. **[Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning](https://md.research.elamur.ai/free/en/papers/wan-2026-test-time-scaling-multimodal-foundation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cong Wan, Ying He, Zhongzhan Huang, et al.*2026*
70. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenyi Xiao, Xinchi XU, Leilei Gan*2026*

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