---
title: "Who cites Aran Komatsuzaki — 343 papers of our library"
description: "343 papers of the Elamur Research library cite the works of Aran Komatsuzaki, found in their bibliographies · page 1 of 2 · 1–100; the most…"
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---
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# Who cites Aran Komatsuzaki

343 citations of their works from 343 papers of our library (of the 149,439 whose bibliographies we read) · 103 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Aran Komatsuzaki](https://md.research.elamur.ai/free/en/authors/aran-komatsuzaki/)

**1** [2](https://md.research.elamur.ai/free/en/authors/aran-komatsuzaki/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/aran-komatsuzaki/cited-by/page/2/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. [**Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding arXiv:2205.11487**Chitwan Saharia, William Chan, Saurabh Saxena, et al.*2022 · 2,533 citations*](https://md.research.elamur.ai/free/en/papers/saharia-2022-photorealistic-text-image-diffusion-models/)
4. [**Flamingo: a Visual Language Model for Few-Shot Learning arXiv:2204.14198**Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.*2022 · 2,246 citations*](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)
5. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,219 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
6. [**High-Resolution Image Synthesis with Latent Diffusion Models arXiv:2112.10752**Robin Rombach, Andreas Blattmann, Dominik Lorenz, et al.*2021 · 1,996 citations*](https://md.research.elamur.ai/free/en/papers/rombach-2021-high-resolution-image-synthesis-latent/)
7. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation arXiv:2201.12086**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,523 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
8. [**DINOv2: Learning Robust Visual Features without Supervision arXiv:2304.07193**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
9. [**LAION-5B: An open large-scale dataset for training next generation image-text models arXiv:2210.08402**Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.*2022 · 1,485 citations*](https://md.research.elamur.ai/free/en/papers/schuhmann-2022-laion-5b-open-large-scale/)
10. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
11. **[Vision-Language Models for Vision Tasks: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-vision-language-models-vision-tasks/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Jingyi Zhang, Jiaxing Huang, Sheng Jin, et al.*2023 · 1,047 citations*
12. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,026 citations*
13. **[ImageBind: One Embedding Space To Bind Them All](https://md.research.elamur.ai/free/en/papers/girdhar-2023-imagebind-one-embedding-space-bind/) [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/)**Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, et al.*2023 · 954 citations*
14. **[Reproducible scaling laws for contrastive language-image learning](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/) [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/)**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 769 citations*
15. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
16. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 467 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
17. **[ShareGPT4V: Improving Large Multi-Modal Models with Better Captions](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 454 citations*
18. [**mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality arXiv:2304.14178**Qinghao Ye, Haiyang Xu, Guohai Xu, et al.*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl-modularization-empowers-large/)
19. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
20. [**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/)
21. [**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/)
22. **[Language Is Not All You Need: Aligning Perception with Language Models](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 330 citations*
23. **[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*
24. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 280 citations*
25. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
26. [**Wan: Open and Advanced Large-Scale Video Generative Models arXiv:2503.20314**Team Wan, Ang Wang, Baole Ai, et al.*2025 · 260 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-wan-open-advanced-large-scale/)
27. [**LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model arXiv:2304.15010**Peng Gao, Jiaming Han, Renrui Zhang, et al.*2023 · 229 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-llama-adapter-v2-parameter-efficient/)
28. **[DataComp: In search of the next generation of multimodal datasets](https://md.research.elamur.ai/free/en/papers/gadre-2023-datacomp-search-next-generation-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.*2023 · 224 citations*
29. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
30. **[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*
31. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning arXiv:2310.09478**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
32. **[MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text](https://md.research.elamur.ai/free/en/papers/chen-2022-murag-multimodal-retrieval-augmented-generator/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Hexiang Hu, Xi Chen, et al.*2022 · 199 citations*
33. **[OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 197 citations*
34. [**LawBench: Benchmarking Legal Knowledge of Large Language Models arXiv:2309.16289**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 188 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
35. **[Are aligned neural networks adversarially aligned?](https://md.research.elamur.ai/free/en/papers/carlini-2023-aligned-neural-networks-adversarially-aligned/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.*2023 · 157 citations*
36. [**MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge arXiv:2206.08853**Linxi Fan, Guanzhi Wang, Yunfan Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/fan-2022-minedojo-building-open-ended-embodied/)
37. [**AudioLDM: Text-to-Audio Generation with Latent Diffusion Models arXiv:2301.12503**Haohe Liu, Zehua Chen, Yi Yuan, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-audioldm-text-audio-generation-latent/)
38. [**InternVideo: General Video Foundation Models via Generative and Discriminative Learning arXiv:2212.03191**Yi Wang, Kunchang Li, Yizhuo Li, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-internvideo-general-video-foundation/)
39. [**Detecting Language Model Attacks with Perplexity arXiv:2308.14132**Gabriel Alon, Michael Kamfonas*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/)
40. **[Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 129 citations*
41. [**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/)
42. [**Platypus: Quick, Cheap, and Powerful Refinement of LLMs arXiv:2308.07317**Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz*2023 · 117 citations*](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/)
43. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
44. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 108 citations*
45. [**SemDeDup: Data-efficient learning at web-scale through semantic deduplication arXiv:2303.09540**Amro Abbas, Kushal Tirumala, Dániel Simig, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/)
46. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
47. [**Arcee's MergeKit: A Toolkit for Merging Large Language Models arXiv:2403.13257**Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/goddard-2024-arcee-s-mergekit-toolkit-merging/)
48. [**FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI arXiv:2411.04872**Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/glazer-2024-frontiermath-benchmark-evaluating-advanced-mathematical/)
49. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
50. [**Retrieval Head Mechanistically Explains Long-Context Factuality arXiv:2404.15574**Wenhao Wu, Yizhong Wang, Guangxuan Xiao, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-head-mechanistically-explains-long/)
51. [**Accelerating Distributed MoE Training and Inference with Lina arXiv:2210.17223**Jiamin Li, Yimin Jiang, Yibo Zhu, et al.*2022 · 92 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-accelerating-distributed-moe-training-inference/)
52. **[Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards](https://md.research.elamur.ai/free/en/papers/rame-2023-rewarded-soups-towards-pareto-optimal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.*2023 · 90 citations*
53. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
54. [**InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition arXiv:2309.15112**Pan Zhang, Xiaoyi Dong, Bin Wang, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-internlm-xcomposer-vision-language/)
55. [**PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis arXiv:2310.00426**Junsong Chen, Jincheng Yu, Chongjian Ge, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-pixart-alpha-fast-training-diffusion/)
56. [**PaperBench: Evaluating AI's Ability to Replicate AI Research arXiv:2504.01848**Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.*2025 · 86 citations*](https://md.research.elamur.ai/free/en/papers/starace-2025-paperbench-evaluating-ai-s/)
57. **[Evaluating Mathematical Reasoning Beyond Accuracy](https://md.research.elamur.ai/free/en/papers/xia-2024-evaluating-mathematical-reasoning-accuracy/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Shijie Xia, Xuefeng Li, Yixin Liu, et al.*2024 · 85 citations*
58. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Zhu, Xiaoye Qu, Daize Dong, et al.*2024 · 85 citations*
59. [**HelpSteer2: Open-source dataset for training top-performing reward models arXiv:2406.08673**Zhilin Wang, Yi Dong, Olivier Delalleau, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer2-open-source-dataset-training/)
60. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
61. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
62. [**Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models arXiv:2305.14705**Sheng Shen, Le Hou, Yanqi Zhou, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-mixture-experts-meets-instruction-tuning/)
63. [**Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning arXiv:2309.05444**Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/zadouri-2023-pushing-mixture-experts-limit-extremely/)
64. [**OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models arXiv:2402.01739**Fuzhao Xue, Zian Zheng, Yao Fu, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/xue-2024-openmoe-early-effort-open-mixture/)
65. [**ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models arXiv:2402.11684**Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-allava-harnessing-gpt4v-synthesized-data/)
66. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
67. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
68. [**DeepSeek-OCR: Contexts Optical Compression arXiv:2510.18234**Haoran Wei, Yaofeng Sun, Yukun Li*2025 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-deepseek-ocr-contexts-optical/)
69. **[InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-4khd-pioneering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 54 citations*
70. [**CMB: A Comprehensive Medical Benchmark in Chinese arXiv:2308.08833**Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-cmb-comprehensive-medical-benchmark/)
71. [**CogVLM2: Visual Language Models for Image and Video Understanding arXiv:2408.16500**Wenyi Hong, Weihan Wang, Ming Ding, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/hong-2024-cogvlm2-visual-language-models/)
72. [**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/)
73. [**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/)
74. [**Stable LM 2 1.6B Technical Report arXiv:2402.17834**Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/bellagente-2024-stable-lm-2-1-6b/)
75. [**GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements arXiv:2402.10963**Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-glore-where-improve-llm-reasoning/)
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