---
title: "Who cites Cheng-Lin Liu — 183 papers of our library"
description: "183 papers of the Elamur Research library cite the works of Cheng-Lin Liu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/cheng-lin-liu/cited-by/"
---
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# Who cites Cheng-Lin Liu

183 citations of their works from 183 papers of our library (of the 149,439 whose bibliographies we read) · 68 with a page here, the most cited first · [← Cheng-Lin Liu](https://md.research.elamur.ai/free/en/authors/cheng-lin-liu/)

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. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [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/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
3. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution arXiv:2409.12191**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 860 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
4. **[How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 541 citations*
5. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts arXiv:2310.02255**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
6. [**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/)
7. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
8. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
9. [**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/)
10. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
11. **[Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models](https://md.research.elamur.ai/free/en/papers/li-2023-monkey-image-resolution-text-label/) [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/)**Zhang Li, Biao Yang, Qiang Liu, et al.*2023 · 222 citations*
12. [**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/)
13. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
14. [**DeepSeek-VL: Towards Real-World Vision-Language Understanding arXiv:2403.05525**Haoyu Lu, Wen Liu, Bo Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-deepseek-vl-real-world/)
15. **[BLINK: Multimodal Large Language Models Can See but Not Perceive](https://md.research.elamur.ai/free/en/papers/fu-2024-blink-multimodal-large-language-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xingyu Fu, Yushi Hu, Bangzheng Li, et al.*2024 · 206 citations*
16. [**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/)
17. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
18. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
19. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
20. **[UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model](https://md.research.elamur.ai/free/en/papers/ye-2023-ureader-universal-ocr-free-visually/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiabo Ye, Anwen Hu, Haiyang Xu, et al.*2023 · 129 citations*
21. **[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*
22. [**MinerU: An Open-Source Solution for Precise Document Content Extraction arXiv:2409.18839**Bin Wang, Chao Xu, Xiaomeng Zhao, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mineru-open-source-solution-precise/)
23. [**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/)
24. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
25. [**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/)
26. [**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/)
27. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations*
28. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
29. [**SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs arXiv:2308.03349**Shengzhi Li, Nima Tajbakhsh*2023 · 50 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-scigraphqa-large-scale-synthetic-multi/)
30. **[Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters More](https://md.research.elamur.ai/free/en/papers/wen-2025-stop-looking-important-tokens-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichen Wen, Yifeng Gao, Shaobo Wang, et al.*2025 · 44 citations*
31. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
32. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
33. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
34. [**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/)
35. [**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/)
36. [**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/)
37. **[Qalam: A Multimodal LLM for Arabic Optical Character and Handwriting Recognition](https://md.research.elamur.ai/free/en/papers/bhatia-2024-qalam-multimodal-llm-arabic-optical/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Gagan Bhatia, El Moatez Billah Nagoudi, Fakhraddin Alwajih, et al.*2024 · 20 citations*
38. [**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/)
39. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
40. **[MMSearch-R1: Incentivizing LMMs to Search](https://md.research.elamur.ai/free/en/papers/wu-2026-mmsearch-r1-incentivizing-lmms-search/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinming Wu, Zihao Deng, Wei Li, et al.*2026 · 16 citations*
41. **[SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement](https://md.research.elamur.ai/free/en/papers/jain-2025-simpledoc-multi-modal-document-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chelsi Jain, Yiran Wu, Yifan Zeng, et al.*2025 · 16 citations*
42. [**HunyuanOCR Technical Report arXiv:2511.19575**Hunyuan Vision Team, Pengyuan Lyu, Xingyu Wan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-vision-hunyuanocr-technical-report/)
43. **[Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better](https://md.research.elamur.ai/free/en/papers/wang-2026-autoregressive-semantic-visual-reconstruction-helps/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dianyi Wang, Wei Song, Yikun Wang, et al.*2026 · 7 citations*
44. **[Benchmarking Vision-Language Models on Chinese Ancient Documents: From OCR to Knowledge Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2026-benchmarking-vision-language-models-chinese/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Yu, Yuchuan Wu, Fan Shi, et al.*2026 · 7 citations*
45. [**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/)
46. **[Revisiting Model Interpolation for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-revisiting-model-interpolation-efficient-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiqiang Wu, Runming Yang, Tao Liu, et al.*2026 · 6 citations*
47. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Lyu Mengsi, Chenrui He, et al.*2026 · 6 citations*
48. [**MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction arXiv:2604.27393**Junbo Cui, Bokai Xu, Chongyi Wang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cui-2026-minicpm-o-4-5/)
49. [**GLM-OCR Technical Report arXiv:2603.10910**Shuaiqi Duan, Yadong Xue, Weihan Wang, et al.*2026 · 4 citations*](https://md.research.elamur.ai/free/en/papers/duan-2026-glm-ocr-technical-report/)
50. **[LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding](https://md.research.elamur.ai/free/en/papers/sourati-2026-lad-rag-layout-aware-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhivar Sourati, Zheng Wang, Marianne Menglin Liu, et al.*2026 · 4 citations*
51. **[a1: Steep Test-time Scaling Law via Environment Augmented Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-a1-steep-test-time-scaling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 2 citations*
52. **[DocLens: A Tool-Augmented Multi-Agent Framework for Long Visual Document Understanding](https://md.research.elamur.ai/free/en/papers/zhu-2026-doclens-tool-augmented-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dawei Zhu, Rui Meng, Jiefeng Chen, et al.*2026 · 2 citations*
53. [**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/)
54. **[Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory](https://md.research.elamur.ai/free/en/papers/tang-2026-mnemis-dual-route-retrieval-hierarchical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Tang, Xin Yu, Ziyu Xiao, et al.*2026 · 1 citation*
55. **[WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2026-wikiseeker-rethinking-role-vision-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingjian Zhu, Xinming Wang, Kun Ding, et al.*2026 · 1 citation*
56. [**Multi-Agent Interactive Question Generation Framework for Long Document Understanding arXiv:2507.20145**Kesen Wang, Daulet Toibazar, Abdulrahman Alfulayt, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/wang-2025-multi-agent-interactive-question-generation/)
57. **[ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents](https://md.research.elamur.ai/free/en/papers/yang-2026-alden-reinforcement-learning-active-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Terry Ruas, Yijun Tian, et al.*2026*
58. **[Attention as Selector: Unlocking VLM Attention for Long Document Page Retrieval](https://md.research.elamur.ai/free/en/papers/zhu-2026-attention-as-selector-unlocking-vlm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minfeng Zhu, Linxin Bao, Wei Chen, et al.*2026*
59. **[Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point Formats](https://md.research.elamur.ai/free/en/papers/zhang-2026-benchmarking-post-training-quantization-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Manyi Zhang, Ji-Fu Li, Zhongao Sun, et al.*2026*
60. **[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*
61. **[DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents](https://md.research.elamur.ai/free/en/papers/shi-2026-damo-data-mixing-optimizer-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Shi, Jun Yang, Ni Yang, et al.*2026*
62. **[Doc-V*: Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA](https://md.research.elamur.ai/free/en/papers/zheng-2026-doc-v-coarse-fine-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanlei Zheng, Pei Fu, Hang Li, et al.*2026*
63. **[MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/xiang-2026-mab-dqa-addressing-query-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Xiang, Yunshan Ma, Xiaoyu Du, et al.*2026*
64. **[MA²P: A Meta-Cognitive Autonomous Intelligent Agents Framework for Complex Persuasion](https://md.research.elamur.ai/free/en/papers/zhang-2026-ma-2-p-meta-cognitive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingyi Zhang, Ziqing Zhuang, Linhai Zhang, et al.*2026*
65. **[Reducing Token Redundancy in LVLMs: A Systematic Review of Token Pruning Methods](https://md.research.elamur.ai/free/en/papers/yuan-2026-reducing-token-redundancy-lvlms-systematic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanzhang Yuan, Mengxuan Hu, Wenhao Zhang, et al.*2026*
66. **[Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-law-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFan Zhang, Tao Yu, Feng Li, et al.*2026*
67. **[When Good OCR Is Not Enough: Benchmarking OCR Robustness for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-when-good-ocr-is-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lin Sun, Wangdexian, Jingang Huang, et al.*2026*
68. **[-SEA³-QA: A Fully Automated Self-Evolving, Adversarial Workflow for Arabic Long-Context Question-Answer Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-mathbfa-sea-3-mathbfl-qa/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Kesen Wang, Daulet Toibazar, Pedro J Moreno Mengibar*2025*

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