🧑‍🔬 Who cites Yonatan Bitton

509 citations of their works from 485 papers of our library (of the 149,439 whose bibliographies we read) · 99 with a page here, the most cited first · ← Yonatan Bitton

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
3. MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIIEEE Computer Society Conference on Computer Vision and Pattern RecognitionXiang Yue, Yuansheng Ni, Kai Zhang, et al.2023 · 1,005 citations
4. Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondarXiv:2308.12966Jinze Bai, Shuai Bai, Shusheng Yang, et al.2023 · 970 citations
5. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
6. ShareGPT4V: Improving Large Multi-Modal Models with Better CaptionsLecture notes in computer scienceLin Chen, Jinsong Li, Xiaoyi Dong, et al.2023 · 454 citations
7. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
8. Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video AnalysisIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChaoyou Fu, Yuhan Dai, Yongdong Luo, et al.2024 · 427 citations
9. CogVLM: Visual Expert for Pretrained Language ModelsConference on Neural Information Processing Systems (NeurIPS)Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.2023 · 383 citations
10. MM-Vet: Evaluating Large Multimodal Models for Integrated CapabilitiesarXiv:2308.02490Weihao Yu, Zhengyuan Yang, Linjie Li, et al.2023 · 344 citations
11. 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
12. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
13. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
14. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
15. 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
16. 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
17. Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
18. OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text DocumentsConference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.2023 · 197 citations
19. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
20. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
21. Aligning Large Multimodal Models with Factually Augmented RLHFarXiv:2309.14525Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.2023 · 176 citations
22. MiniCheck: Efficient Fact-Checking of LLMs on Grounding DocumentsConference on Empirical Methods in Natural Language Processing (EMNLP)Liyan Tang, Philippe Laban, Greg Durrett2024 · 166 citations
23. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
24. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
25. Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Li, Yuqi Wang, Runxin Xu, et al.2024 · 129 citations
26. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
27. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
28. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
29. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
30. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
31. InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large ModelarXiv:2401.16420Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 94 citations
32. GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningarXiv:2507.01006GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.2025 · 89 citations
33. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
34. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
35. 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
36. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
37. Kimi-VL Technical ReportarXiv:2504.07491Kimi Team, Angang Du, Bohong Yin, et al.2025 · 70 citations
38. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
39. VIEScore: Towards Explainable Metrics for Conditional Image Synthesis EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Max Ku, Dongfu Jiang, Cong Wei, et al.2024 · 68 citations
40. Kimi K2.5: Visual Agentic IntelligencearXiv:2602.02276Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 66 citations
41. Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Su, Kezhi Kong, Ying Lin, et al.2025 · 65 citations
42. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningarXiv:2509.06888Marc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
43. MMICL: Empowering Vision-language Model with Multi-Modal In-Context LearningarXiv:2309.07915Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.2023 · 58 citations
44. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
45. In-context Learning with Retrieved Demonstrations for Language Models: A SurveyarXiv:2401.11624Man Luo, Xin Xu, Yue Liu, et al.2024 · 54 citations
46. 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
47. M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Qiguang Chen, Libo Qin, Jin Zhang, et al.2024 · 54 citations
48. CogVLM2: Visual Language Models for Image and Video UnderstandingarXiv:2408.16500Wenyi Hong, Weihan Wang, Ming Ding, et al.2024 · 52 citations
49. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
50. Language models scale reliably with over-training and on downstream tasksarXiv:2403.08540Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.2024 · 46 citations
51. Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesarXiv:2407.13623Chaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 46 citations
52. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsarXiv:2502.18443Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.2025 · 44 citations
53. Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters MoreConference on Empirical Methods in Natural Language Processing (EMNLP)Zichen Wen, Yifeng Gao, Shaobo Wang, et al.2025 · 44 citations
54. NVLM: Open Frontier-Class Multimodal LLMsarXiv:2409.11402Wenliang Dai, Nayeon Lee, Boxin Wang, et al.2024 · 44 citations
55. 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
56. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
57. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
58. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
59. MegaPairs: Massive Data Synthesis for Universal Multimodal RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Junjie Zhou, Yongping Xiong, Zheng Liu, et al.2025 · 26 citations
60. 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
61. RWKV-7 "Goose" with Expressive Dynamic State EvolutionarXiv:2503.14456Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.2025 · 23 citations
62. MiniCPM4: Ultra-Efficient LLMs on End DevicesarXiv:2506.07900MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.2025 · 22 citations
63. Scaling Latent Reasoning via Looped Language ModelsarXiv:2510.25741Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.2025 · 22 citations
64. TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence ConfigurationConference on Empirical Methods in Natural Language Processing (EMNLP)Yanshu Li, Jianjiang Yang, Tian Yun, et al.2025 · 22 citations
65. Baichuan-Omni Technical ReportarXiv:2410.08565Yadong Li, Haoze Sun, Mingan Lin, et al.2024 · 18 citations
66. Dataset Decomposition: Faster LLM Training with Variable Sequence Length CurriculumConference on Neural Information Processing Systems (NeurIPS)Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.2024 · 16 citations
67. Measuring Chain of Thought Faithfulness by Unlearning Reasoning StepsConference on Empirical Methods in Natural Language Processing (EMNLP)Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.2025 · 15 citations
68. Rethinking Reflection in Pre-TrainingarXiv:2504.04022Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.2025 · 15 citations
69. Understanding Chain-of-Thought in LLMs through Information TheoryarXiv:2411.11984Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu2024 · 14 citations
70. VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual CuesAnnual Meeting of the Association for Computational Linguistics (ACL)Jianshu Zhang, Dongyu Yao, Renjie Pi, et al.2025 · 12 citations
71. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
72. MiniPLM: Knowledge Distillation for Pre-Training Language ModelsarXiv:2410.17215Yuxian Gu, Hao Zhou, Fandong Meng, et al.2024 · 12 citations
73. Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation FrameworkConference on Empirical Methods in Natural Language Processing (EMNLP)Mohna Chakraborty, Lu Wang, David Jurgens2025 · 9 citations
74. Arabic Stable LM: Adapting Stable LM 2 1.6B to ArabicarXiv:2412.04277Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.2024 · 6 citations
75. Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?International Joint Conference on Natural Language Processing (IJCNLP)Kai Yan, Yufei Xu, Zhengyin Du, et al.2025 · 5 citations
76. Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generationConference of the European Chapter of the Association for Computational Linguistics (EACL)Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.2026 · 4 citations
77. QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsDehai Min, Kailin Zhang, Tongtong Wu, et al.2026 · 2 citations
78. The olmOCR Project: Building Fully Open OCR using VLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jake Poznanski, Kyle Lo, Luca Soldaini2026 · 2 citations
79. Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Boxuan Wang, Zhuoyun Li, Xinmiao Huang, et al.2026 · 1 citation
80. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
81. FaithLens: Detecting and Explaining Faithfulness HallucinationFindings of the Association for Computational LinguisticsShuzheng Si, Qingyi Wang, Haozhe Zhao, et al.2026 · 1 citation
82. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full ReportarXiv:2606.03773Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.2026 · 1 citation
83. Reformulate and Create, Don't Translate: Creating Natural Prompts for Underserved LanguagesLanguage Resources and Evaluation Conference (LREC)Annika Simonsen, Mathias Stenlund, Lars Bungum, et al.2026 · 1 citation
84. Revisiting Audio-language Pretraining for Learning General-purpose Audio RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Wei-Cheng Tseng, Xuanru Zhou, Mingyue Huo, et al.2026 · 1 citation
85. The Thin Line Between Comprehension and Persuasion in LLMsFindings of the Association for Computational LinguisticsAdrian de Wynter, Tangming Yuan2026 · 1 citation
86. A Parameter-Efficient and Data-Centric Framework for Ancient Chinese Text Recognition and Layout AnalysisWorkshop on Language Technologies for Historical and Ancient Languages @ LRECYuchun Meng2026
87. Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level AnnotationFindings of the Association for Computational LinguisticsRian Touchent, Nathan Godey, Éric Villemonte de la Clergerie2026
88. Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual DataLanguage Resources and Evaluation Conference (LREC)Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.2026
89. Journey Before Destination: On the importance of Visual Faithfulness in Slow ThinkingConference of the European Chapter of the Association for Computational Linguistics (EACL)Rheeya Uppaal, Phu Mon Htut, Min Bai, et al.2026
90. KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?Transactions of the Association for Computational Linguistics (TACL)Soumadeep Saha, Akshay Chaturvedi, Saptarshi Saha, et al.2026
91. Multilingual-To-Multimodal (M2M): Unlocking New Languages with Monolingual TextFindings of the Association for Computational LinguisticsPiyush Singh Pasi2026
92. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
93. Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model BehaviorTransactions of the Association for Computational Linguistics (TACL)Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.2026
94. S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language ModelsFindings of the Association for Computational LinguisticsNitish Shukla, Surgan Jandial, Arun Ross2026
95. SciPedia: Unlocking the Value of Scientific Data for Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yiwei Qin, Zhen Huang, Tiantian Mi, et al.2026
96. SELECting over Tokens: Curating Pre-training Data at Scale via Token ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Tong, Weidong Zhang, Jiaang Li, et al.2026
97. Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool CompositionAnnual Meeting of the Association for Computational Linguistics (ACL)Ye Wang, Qianglong Chen, Siyuan Wang, et al.2026
98. Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note ScaleBioNLPJinghui Liu, Sarvesh Soni, Anthony Nguyen2026
99. When Seeing Is not Enough: Revealing the Limits of Active Reasoning in MLLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Hongcheng Liu, Pingjie Wang, Yuhao Wang, et al.2026

386 more citing papers of our library have no page here yet.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yonatan-bitton/cited-by/